Overview

Brought to you by YData

Dataset statistics

 Full DatasetSimple Random Sample
Number of variables7878
Number of observations100000030000
Missing cells00
Missing cells (%)0.0%0.0%
Total size in memory595.1 MiB17.9 MiB
Average record size in memory624.0 B624.0 B

Variable types

 Full DatasetSimple Random Sample
Numeric4040
Text3838

Alerts

Full DatasetSimple Random Sample
customer_id has unique values customer_id has unique values Unique
membership_years has 99846 (10.0%) zeros membership_years has 2958 (9.9%) zeros Zeros
number_of_children has 199753 (20.0%) zeros number_of_children has 6017 (20.1%) zeros Zeros
transaction_hour has 41756 (4.2%) zeros transaction_hour has 1259 (4.2%) zeros Zeros
avg_discount_used has 10010 (1.0%) zeros avg_discount_used has 302 (1.0%) zeros Zeros
in_store_purchases has 10016 (1.0%) zeros Alert not present in this datasetZeros
total_returned_items has 100060 (10.0%) zeros total_returned_items has 3135 (10.4%) zeros Zeros
product_stock has 10174 (1.0%) zeros product_stock has 350 (1.2%) zeros Zeros
customer_support_calls has 49755 (5.0%) zeros customer_support_calls has 1519 (5.1%) zeros Zeros
website_visits has 10111 (1.0%) zeros Alert not present in this datasetZeros
Alert not present in this datasetdiscount_applied has 308 (1.0%) zeros Zeros

Reproduction

 Full DatasetSimple Random Sample
Analysis started2025-06-06 01:52:54.3770342025-06-06 01:54:48.463188
Analysis finished2025-06-06 01:54:48.4325652025-06-06 01:54:52.061982
Duration1 minute and 54.06 seconds3.6 seconds
Software versionydata-profiling vv4.16.1ydata-profiling vv4.16.1
Download configurationconfig.jsonconfig.json

Variables

customer_id
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100000030000
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500000.5498341.3221
 Full DatasetSimple Random Sample
Minimum132
Maximum1000000999998
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:52.559455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum132
5-th percentile50000.9549982.45
Q1250000.75247346.5
median500000.5497046.5
Q3750000.25749722.25
95-th percentile950000.05950257.2
Maximum1000000999998
Range999999999966
Interquartile range (IQR)499999.5502375.75

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288675.2789289118.6274
Coefficient of variation (CV)0.57734998050.580161858
Kurtosis-1.2-1.202680509
Mean500000.5498341.3221
Median Absolute Deviation (MAD)250000251080
Skewness-2.511790261 × 10-150.01105143153
Sum5.000005 × 10111.495023966 × 1010
Variance8.333341667 × 10108.358958069 × 1010
MonotonicityStrictly increasingNot monotonic
2025-06-06T01:54:52.796338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
999984 1
 
< 0.1%
999983 1
 
< 0.1%
999982 1
 
< 0.1%
999981 1
 
< 0.1%
999980 1
 
< 0.1%
999979 1
 
< 0.1%
999978 1
 
< 0.1%
999977 1
 
< 0.1%
999976 1
 
< 0.1%
999975 1
 
< 0.1%
Other values (999990) 999990
> 99.9%
ValueCountFrequency (%)
547377 1
 
< 0.1%
283863 1
 
< 0.1%
1689 1
 
< 0.1%
298935 1
 
< 0.1%
587245 1
 
< 0.1%
920175 1
 
< 0.1%
847679 1
 
< 0.1%
363616 1
 
< 0.1%
548643 1
 
< 0.1%
399591 1
 
< 0.1%
Other values (29990) 29990
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
ValueCountFrequency (%)
32 1
< 0.1%
79 1
< 0.1%
103 1
< 0.1%
147 1
< 0.1%
186 1
< 0.1%
ValueCountFrequency (%)
32 1
< 0.1%
79 1
< 0.1%
103 1
< 0.1%
147 1
< 0.1%
186 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%

age
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct6262
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean48.49660548.52456667
 Full DatasetSimple Random Sample
Minimum1818
Maximum7979
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:53.004391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1818
5-th percentile2121
Q13333
median4949
Q36464
95-th percentile7676
Maximum7979
Range6161
Interquartile range (IQR)3131

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation17.8743811617.89329489
Coefficient of variation (CV)0.36856974140.3687471341
Kurtosis-1.198117884-1.198360533
Mean48.49660548.52456667
Median Absolute Deviation (MAD)1515
Skewness-0.0002769945754-0.004311892695
Sum484966051455737
Variance319.493502320.1700021
MonotonicityNot monotonicNot monotonic
2025-06-06T01:54:53.236509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 16423
 
1.6%
54 16412
 
1.6%
33 16407
 
1.6%
36 16363
 
1.6%
62 16324
 
1.6%
39 16290
 
1.6%
34 16284
 
1.6%
40 16274
 
1.6%
32 16264
 
1.6%
19 16248
 
1.6%
Other values (52) 836711
83.7%
ValueCountFrequency (%)
58 557
 
1.9%
65 543
 
1.8%
19 521
 
1.7%
43 519
 
1.7%
77 516
 
1.7%
33 515
 
1.7%
52 513
 
1.7%
22 512
 
1.7%
42 511
 
1.7%
74 511
 
1.7%
Other values (52) 24782
82.6%
ValueCountFrequency (%)
18 16003
1.6%
19 16248
1.6%
20 16116
1.6%
21 16016
1.6%
22 16211
1.6%
ValueCountFrequency (%)
18 460
1.5%
19 521
1.7%
20 476
1.6%
21 496
1.7%
22 512
1.7%
ValueCountFrequency (%)
18 460
< 0.1%
19 521
0.1%
20 476
< 0.1%
21 496
< 0.1%
22 512
0.1%
ValueCountFrequency (%)
18 16003
53.3%
19 16248
54.2%
20 16116
53.7%
21 16016
53.4%
22 16211
54.0%

gender
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:53.508382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length55
Mean length5.0011745.000633333
Min length44

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters5001174150019
Distinct characters1010
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowOtherFemale
2nd rowFemaleOther
3rd rowFemaleOther
4th rowFemaleOther
5th rowFemaleOther
ValueCountFrequency (%)
other 333734
33.4%
female 333720
33.4%
male 332546
33.3%
ValueCountFrequency (%)
other 10017
33.4%
female 10001
33.3%
male 9982
33.3%
2025-06-06T01:54:53.872544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 40001
26.7%
a 19983
13.3%
l 19983
13.3%
O 10017
 
6.7%
t 10017
 
6.7%
h 10017
 
6.7%
r 10017
 
6.7%
F 10001
 
6.7%
m 10001
 
6.7%
M 9982
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150019
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 40001
26.7%
a 19983
13.3%
l 19983
13.3%
O 10017
 
6.7%
t 10017
 
6.7%
h 10017
 
6.7%
r 10017
 
6.7%
F 10001
 
6.7%
m 10001
 
6.7%
M 9982
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150019
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 40001
26.7%
a 19983
13.3%
l 19983
13.3%
O 10017
 
6.7%
t 10017
 
6.7%
h 10017
 
6.7%
r 10017
 
6.7%
F 10001
 
6.7%
m 10001
 
6.7%
M 9982
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150019
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 40001
26.7%
a 19983
13.3%
l 19983
13.3%
O 10017
 
6.7%
t 10017
 
6.7%
h 10017
 
6.7%
r 10017
 
6.7%
F 10001
 
6.7%
m 10001
 
6.7%
M 9982
 
6.7%

income_bracket
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:54.060706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length44
Mean length4.3337134.342766667
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters4333713130283
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowHighMedium
2nd rowMediumLow
3rd rowLowMedium
4th rowLowHigh
5th rowLowMedium
ValueCountFrequency (%)
high 333612
33.4%
medium 333367
33.3%
low 333021
33.3%
ValueCountFrequency (%)
medium 10133
33.8%
low 9983
33.3%
high 9884
32.9%
2025-06-06T01:54:54.608666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20017
15.4%
M 10133
7.8%
e 10133
7.8%
d 10133
7.8%
u 10133
7.8%
m 10133
7.8%
L 9983
7.7%
o 9983
7.7%
w 9983
7.7%
H 9884
7.6%
Other values (2) 19768
15.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130283
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20017
15.4%
M 10133
7.8%
e 10133
7.8%
d 10133
7.8%
u 10133
7.8%
m 10133
7.8%
L 9983
7.7%
o 9983
7.7%
w 9983
7.7%
H 9884
7.6%
Other values (2) 19768
15.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130283
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20017
15.4%
M 10133
7.8%
e 10133
7.8%
d 10133
7.8%
u 10133
7.8%
m 10133
7.8%
L 9983
7.7%
o 9983
7.7%
w 9983
7.7%
H 9884
7.6%
Other values (2) 19768
15.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130283
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20017
15.4%
M 10133
7.8%
e 10133
7.8%
d 10133
7.8%
u 10133
7.8%
m 10133
7.8%
L 9983
7.7%
o 9983
7.7%
w 9983
7.7%
H 9884
7.6%
Other values (2) 19768
15.2%

loyalty_program
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:54.747325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length33
Median length23
Mean length2.4997122.502266667
Min length22

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters249971275068
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowNoYes
2nd rowNoNo
3rd rowNoYes
4th rowNoYes
5th rowYesNo
ValueCountFrequency (%)
no 500288
50.0%
yes 499712
50.0%
ValueCountFrequency (%)
yes 15068
50.2%
no 14932
49.8%
2025-06-06T01:54:55.001647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
Y 15068
20.1%
e 15068
20.1%
s 15068
20.1%
N 14932
19.9%
o 14932
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 75068
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
Y 15068
20.1%
e 15068
20.1%
s 15068
20.1%
N 14932
19.9%
o 14932
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 75068
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
Y 15068
20.1%
e 15068
20.1%
s 15068
20.1%
N 14932
19.9%
o 14932
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 75068
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
Y 15068
20.1%
e 15068
20.1%
s 15068
20.1%
N 14932
19.9%
o 14932
19.9%

membership_years
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct1010
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.4974534.491533333
 Full DatasetSimple Random Sample
Minimum00
Maximum99
Zeros998462958
Zeros (%)10.0%9.9%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:55.099128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile00
Q122
median45
Q377
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)55

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.8724055712.863983542
Coefficient of variation (CV)0.63867383850.6376404959
Kurtosis-1.22454665-1.224137652
Mean4.4974534.491533333
Median Absolute Deviation (MAD)33
Skewness0.001590463324-0.003298623147
Sum4497453134746
Variance8.2507137648.202401729
MonotonicityNot monotonicNot monotonic
2025-06-06T01:54:55.205081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 100686
10.1%
5 100183
10.0%
4 100137
10.0%
9 99977
10.0%
2 99964
10.0%
8 99891
10.0%
6 99865
10.0%
0 99846
10.0%
7 99728
10.0%
3 99723
10.0%
ValueCountFrequency (%)
1 3096
10.3%
5 3075
10.2%
6 3075
10.2%
8 3030
10.1%
2 3028
10.1%
7 2995
10.0%
4 2977
9.9%
0 2958
9.9%
9 2893
9.6%
3 2873
9.6%
ValueCountFrequency (%)
0 99846
10.0%
1 100686
10.1%
2 99964
10.0%
3 99723
10.0%
4 100137
10.0%
ValueCountFrequency (%)
0 2958
9.9%
1 3096
10.3%
2 3028
10.1%
3 2873
9.6%
4 2977
9.9%
ValueCountFrequency (%)
0 2958
0.3%
1 3096
0.3%
2 3028
0.3%
3 2873
0.3%
4 2977
0.3%
ValueCountFrequency (%)
0 99846
332.8%
1 100686
335.6%
2 99964
333.2%
3 99723
332.4%
4 100137
333.8%

churned
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:55.361583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length33
Median length22
Mean length2.4997292.496233333
Min length22

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters249972974887
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowNoYes
2nd rowNoYes
3rd rowNoNo
4th rowNoNo
5th rowYesNo
ValueCountFrequency (%)
no 500271
50.0%
yes 499729
50.0%
ValueCountFrequency (%)
no 15113
50.4%
yes 14887
49.6%
2025-06-06T01:54:55.642395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15113
20.2%
o 15113
20.2%
Y 14887
19.9%
e 14887
19.9%
s 14887
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74887
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15113
20.2%
o 15113
20.2%
Y 14887
19.9%
e 14887
19.9%
s 14887
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74887
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15113
20.2%
o 15113
20.2%
Y 14887
19.9%
e 14887
19.9%
s 14887
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74887
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15113
20.2%
o 15113
20.2%
Y 14887
19.9%
e 14887
19.9%
s 14887
19.9%

marital_status
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:55.837340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length88
Median length77
Mean length7.0008666.999766667
Min length66

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters7000866209993
Distinct characters1414
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowDivorcedDivorced
2nd rowMarriedSingle
3rd rowMarriedSingle
4th rowDivorcedDivorced
5th rowDivorcedSingle
ValueCountFrequency (%)
divorced 333816
33.4%
married 333234
33.3%
single 332950
33.3%
ValueCountFrequency (%)
married 10103
33.7%
single 9952
33.2%
divorced 9945
33.1%
2025-06-06T01:54:56.152710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30151
14.4%
i 30000
14.3%
e 30000
14.3%
d 20048
9.5%
a 10103
 
4.8%
M 10103
 
4.8%
S 9952
 
4.7%
n 9952
 
4.7%
g 9952
 
4.7%
l 9952
 
4.7%
Other values (4) 39780
18.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 209993
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30151
14.4%
i 30000
14.3%
e 30000
14.3%
d 20048
9.5%
a 10103
 
4.8%
M 10103
 
4.8%
S 9952
 
4.7%
n 9952
 
4.7%
g 9952
 
4.7%
l 9952
 
4.7%
Other values (4) 39780
18.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 209993
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30151
14.4%
i 30000
14.3%
e 30000
14.3%
d 20048
9.5%
a 10103
 
4.8%
M 10103
 
4.8%
S 9952
 
4.7%
n 9952
 
4.7%
g 9952
 
4.7%
l 9952
 
4.7%
Other values (4) 39780
18.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 209993
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30151
14.4%
i 30000
14.3%
e 30000
14.3%
d 20048
9.5%
a 10103
 
4.8%
M 10103
 
4.8%
S 9952
 
4.7%
n 9952
 
4.7%
g 9952
 
4.7%
l 9952
 
4.7%
Other values (4) 39780
18.9%

number_of_children
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.0005541.988633333
 Full DatasetSimple Random Sample
Minimum00
Maximum44
Zeros1997536017
Zeros (%)20.0%20.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:56.253793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile00
Q111
median22
Q333
95-th percentile44
Maximum44
Range44
Interquartile range (IQR)22

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation1.4142141611.409410165
Coefficient of variation (CV)0.70691126610.7087330487
Kurtosis-1.300270709-1.292392756
Mean2.0005541.988633333
Median Absolute Deviation (MAD)11
Skewness-0.00012232956460.009062593281
Sum200055459659
Variance2.0000016931.986437013
MonotonicityNot monotonicNot monotonic
2025-06-06T01:54:56.351398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
1 200307
20.0%
4 200157
20.0%
3 200053
20.0%
0 199753
20.0%
2 199730
20.0%
ValueCountFrequency (%)
1 6055
20.2%
2 6042
20.1%
3 6024
20.1%
0 6017
20.1%
4 5862
19.5%
ValueCountFrequency (%)
0 199753
20.0%
1 200307
20.0%
2 199730
20.0%
3 200053
20.0%
4 200157
20.0%
ValueCountFrequency (%)
0 6017
20.1%
1 6055
20.2%
2 6042
20.1%
3 6024
20.1%
4 5862
19.5%
ValueCountFrequency (%)
0 6017
0.6%
1 6055
0.6%
2 6042
0.6%
3 6024
0.6%
4 5862
0.6%
ValueCountFrequency (%)
0 199753
665.8%
1 200307
667.7%
2 199730
665.8%
3 200053
666.8%
4 200157
667.2%

education_level
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:56.639054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1111
Median length1010
Mean length8.000647.961
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters8000640238830
Distinct characters1919
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowBachelor'sMaster's
2nd rowPhDHigh School
3rd rowBachelor'sHigh School
4th rowMaster'sMaster's
5th rowBachelor'sMaster's
ValueCountFrequency (%)
bachelor's 250360
20.0%
high 250105
20.0%
school 250105
20.0%
phd 250079
20.0%
master's 249456
20.0%
ValueCountFrequency (%)
phd 7662
20.5%
bachelor's 7494
20.0%
master's 7460
20.0%
high 7384
19.8%
school 7384
19.8%
2025-06-06T01:54:57.146166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29924
12.5%
s 22414
 
9.4%
o 22262
 
9.3%
' 14954
 
6.3%
e 14954
 
6.3%
r 14954
 
6.3%
a 14954
 
6.3%
l 14878
 
6.2%
c 14878
 
6.2%
D 7662
 
3.2%
Other values (9) 66996
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 238830
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29924
12.5%
s 22414
 
9.4%
o 22262
 
9.3%
' 14954
 
6.3%
e 14954
 
6.3%
r 14954
 
6.3%
a 14954
 
6.3%
l 14878
 
6.2%
c 14878
 
6.2%
D 7662
 
3.2%
Other values (9) 66996
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 238830
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29924
12.5%
s 22414
 
9.4%
o 22262
 
9.3%
' 14954
 
6.3%
e 14954
 
6.3%
r 14954
 
6.3%
a 14954
 
6.3%
l 14878
 
6.2%
c 14878
 
6.2%
D 7662
 
3.2%
Other values (9) 66996
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 238830
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29924
12.5%
s 22414
 
9.4%
o 22262
 
9.3%
' 14954
 
6.3%
e 14954
 
6.3%
r 14954
 
6.3%
a 14954
 
6.3%
l 14878
 
6.2%
c 14878
 
6.2%
D 7662
 
3.2%
Other values (9) 66996
28.1%

occupation
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:57.491471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1313
Median length1010
Mean length9.5008549.519233333
Min length77

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters9500854285577
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowSelf-EmployedUnemployed
2nd rowUnemployedEmployed
3rd rowSelf-EmployedUnemployed
4th rowEmployedEmployed
5th rowEmployedRetired
ValueCountFrequency (%)
employed 250857
25.1%
unemployed 250117
25.0%
self-employed 249941
25.0%
retired 249085
24.9%
ValueCountFrequency (%)
self-employed 7600
25.3%
unemployed 7520
25.1%
retired 7463
24.9%
employed 7417
24.7%
2025-06-06T01:54:57.979866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52583
18.4%
l 30137
10.6%
d 30000
10.5%
o 22537
7.9%
p 22537
7.9%
y 22537
7.9%
m 22537
7.9%
E 15017
 
5.3%
S 7600
 
2.7%
f 7600
 
2.7%
Other values (7) 52492
18.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285577
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52583
18.4%
l 30137
10.6%
d 30000
10.5%
o 22537
7.9%
p 22537
7.9%
y 22537
7.9%
m 22537
7.9%
E 15017
 
5.3%
S 7600
 
2.7%
f 7600
 
2.7%
Other values (7) 52492
18.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285577
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52583
18.4%
l 30137
10.6%
d 30000
10.5%
o 22537
7.9%
p 22537
7.9%
y 22537
7.9%
m 22537
7.9%
E 15017
 
5.3%
S 7600
 
2.7%
f 7600
 
2.7%
Other values (7) 52492
18.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285577
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52583
18.4%
l 30137
10.6%
d 30000
10.5%
o 22537
7.9%
p 22537
7.9%
y 22537
7.9%
m 22537
7.9%
E 15017
 
5.3%
S 7600
 
2.7%
f 7600
 
2.7%
Other values (7) 52492
18.4%

transaction_id
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct63257629552
Distinct (%)63.3%98.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499891.7314499115.5692
 Full DatasetSimple Random Sample
Minimum211
Maximum999999999919
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:58.242567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum211
5-th percentile50200.9550842.95
Q1249878.75251382.5
median499559.5498323
Q3750071.25748778.5
95-th percentile950045.2950143.55
Maximum999999999919
Range999997999908
Interquartile range (IQR)500192.5497396

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288706.0577288264.9089
Coefficient of variation (CV)0.57753717350.5775514263
Kurtosis-1.200114605-1.191606103
Mean499891.7314499115.5692
Median Absolute Deviation (MAD)250088.5248147
Skewness0.0023951872530.008057397532
Sum4.998917314 × 10111.497346708 × 1010
Variance8.335118772 × 10108.309665769 × 1010
MonotonicityNot monotonicNot monotonic
2025-06-06T01:54:58.564739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
115913 9
 
< 0.1%
504562 8
 
< 0.1%
344167 8
 
< 0.1%
2773 8
 
< 0.1%
239407 8
 
< 0.1%
620816 8
 
< 0.1%
273197 8
 
< 0.1%
254678 7
 
< 0.1%
798940 7
 
< 0.1%
335691 7
 
< 0.1%
Other values (632566) 999922
> 99.9%
ValueCountFrequency (%)
820606 3
 
< 0.1%
596759 3
 
< 0.1%
469458 3
 
< 0.1%
846917 2
 
< 0.1%
297836 2
 
< 0.1%
474299 2
 
< 0.1%
642262 2
 
< 0.1%
754632 2
 
< 0.1%
752631 2
 
< 0.1%
847080 2
 
< 0.1%
Other values (29542) 29977
99.9%
ValueCountFrequency (%)
2 2
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%
ValueCountFrequency (%)
11 1
< 0.1%
108 1
< 0.1%
118 1
< 0.1%
144 1
< 0.1%
177 1
< 0.1%
ValueCountFrequency (%)
11 1
< 0.1%
108 1
< 0.1%
118 1
< 0.1%
144 1
< 0.1%
177 1
< 0.1%
ValueCountFrequency (%)
2 2
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%

transaction_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct99223129989
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:54:59.616408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique98450429978 ?
Unique (%)98.5%99.9%

Sample

 Full DatasetSimple Random Sample
1st row2020-10-11 10:08:522021-02-15 08:17:00
2nd row2021-12-08 01:07:402020-11-30 00:39:49
3rd row2020-02-17 09:40:482021-05-27 22:47:43
4th row2020-08-13 00:43:142020-04-03 06:25:01
5th row2021-07-02 11:59:032021-01-10 15:59:11
ValueCountFrequency (%)
2020-10-05 1509
 
0.1%
2020-09-06 1467
 
0.1%
2020-10-04 1464
 
0.1%
2020-07-26 1463
 
0.1%
2020-02-26 1458
 
0.1%
2020-05-03 1455
 
0.1%
2021-02-27 1453
 
0.1%
2021-07-30 1451
 
0.1%
2020-09-07 1451
 
0.1%
2020-10-09 1447
 
0.1%
Other values (87119) 1985382
99.3%
ValueCountFrequency (%)
2020-03-21 61
 
0.1%
2021-06-29 60
 
0.1%
2020-11-07 59
 
0.1%
2021-04-04 58
 
0.1%
2020-09-29 57
 
0.1%
2021-04-30 56
 
0.1%
2021-12-12 56
 
0.1%
2021-03-05 56
 
0.1%
2020-05-04 55
 
0.1%
2020-02-03 55
 
0.1%
Other values (26147) 59427
99.0%
2025-06-06T01:55:00.378715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 113891
20.0%
2 102464
18.0%
1 73218
12.8%
: 60000
10.5%
- 60000
10.5%
30000
 
5.3%
3 26909
 
4.7%
4 23933
 
4.2%
5 23922
 
4.2%
8 13940
 
2.4%
Other values (3) 41723
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 113891
20.0%
2 102464
18.0%
1 73218
12.8%
: 60000
10.5%
- 60000
10.5%
30000
 
5.3%
3 26909
 
4.7%
4 23933
 
4.2%
5 23922
 
4.2%
8 13940
 
2.4%
Other values (3) 41723
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 113891
20.0%
2 102464
18.0%
1 73218
12.8%
: 60000
10.5%
- 60000
10.5%
30000
 
5.3%
3 26909
 
4.7%
4 23933
 
4.2%
5 23922
 
4.2%
8 13940
 
2.4%
Other values (3) 41723
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 113891
20.0%
2 102464
18.0%
1 73218
12.8%
: 60000
10.5%
- 60000
10.5%
30000
 
5.3%
3 26909
 
4.7%
4 23933
 
4.2%
5 23922
 
4.2%
8 13940
 
2.4%
Other values (3) 41723
 
7.3%

product_id
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct99999502
Distinct (%)1.0%31.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4999.5645154991.183033
 Full DatasetSimple Random Sample
Minimum11
Maximum99999999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:00.556052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile500499
Q124982501
median49994963.5
Q374987474
95-th percentile94999525
Maximum99999999
Range99989998
Interquartile range (IQR)50004973

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2886.7983912882.154274
Coefficient of variation (CV)0.57740996890.5774491247
Kurtosis-1.200144352-1.189994885
Mean4999.5645154991.183033
Median Absolute Deviation (MAD)25002485.5
Skewness0.00023461072220.01509355125
Sum4999564515149735491
Variance8333604.958306813.258
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:01.025793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4898 145
 
< 0.1%
51 143
 
< 0.1%
9593 141
 
< 0.1%
5427 138
 
< 0.1%
3923 137
 
< 0.1%
8365 135
 
< 0.1%
4541 134
 
< 0.1%
2590 134
 
< 0.1%
467 133
 
< 0.1%
3676 133
 
< 0.1%
Other values (9989) 998627
99.9%
ValueCountFrequency (%)
30 11
 
< 0.1%
3338 11
 
< 0.1%
1467 11
 
< 0.1%
1844 11
 
< 0.1%
3944 10
 
< 0.1%
2330 10
 
< 0.1%
4574 10
 
< 0.1%
374 10
 
< 0.1%
2391 10
 
< 0.1%
7730 10
 
< 0.1%
Other values (9492) 29896
99.7%
ValueCountFrequency (%)
1 92
< 0.1%
2 107
< 0.1%
3 117
< 0.1%
4 97
< 0.1%
5 92
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
2 6
< 0.1%
3 7
< 0.1%
4 4
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
2 6
< 0.1%
3 7
< 0.1%
4 4
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
1 92
0.3%
2 107
0.4%
3 117
0.4%
4 97
0.3%
5 92
0.3%

product_category
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:01.330898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1111
Median length99
Mean length8.1963898.232533333
Min length44

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters8196389246976
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowElectronicsGroceries
2nd rowGroceriesToys
3rd rowToysToys
4th rowToysClothing
5th rowClothingGroceries
ValueCountFrequency (%)
toys 200669
20.1%
groceries 200214
20.0%
clothing 199778
20.0%
electronics 199756
20.0%
furniture 199583
20.0%
ValueCountFrequency (%)
electronics 6217
20.7%
clothing 6038
20.1%
groceries 5942
19.8%
furniture 5919
19.7%
toys 5884
19.6%
2025-06-06T01:55:01.680456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 29939
12.1%
i 24116
9.8%
o 24081
9.8%
e 24020
9.7%
c 18376
 
7.4%
t 18174
 
7.4%
n 18174
 
7.4%
s 18043
 
7.3%
l 12255
 
5.0%
u 11838
 
4.8%
Other values (8) 47960
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246976
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 29939
12.1%
i 24116
9.8%
o 24081
9.8%
e 24020
9.7%
c 18376
 
7.4%
t 18174
 
7.4%
n 18174
 
7.4%
s 18043
 
7.3%
l 12255
 
5.0%
u 11838
 
4.8%
Other values (8) 47960
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246976
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 29939
12.1%
i 24116
9.8%
o 24081
9.8%
e 24020
9.7%
c 18376
 
7.4%
t 18174
 
7.4%
n 18174
 
7.4%
s 18043
 
7.3%
l 12255
 
5.0%
u 11838
 
4.8%
Other values (8) 47960
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246976
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 29939
12.1%
i 24116
9.8%
o 24081
9.8%
e 24020
9.7%
c 18376
 
7.4%
t 18174
 
7.4%
n 18174
 
7.4%
s 18043
 
7.3%
l 12255
 
5.0%
u 11838
 
4.8%
Other values (8) 47960
19.4%

quantity
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct99
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.0026495.001833333
 Full DatasetSimple Random Sample
Minimum11
Maximum99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:01.775490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile11
Q133
median55
Q377
95-th percentile99
Maximum99
Range88
Interquartile range (IQR)44

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.5837512762.589437547
Coefficient of variation (CV)0.5164766260.517697687
Kurtosis-1.231080652-1.236452576
Mean5.0026495.001833333
Median Absolute Deviation (MAD)22
Skewness-0.0003647460673-0.0001522943516
Sum5002649150055
Variance6.6757706596.705186812
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:01.877040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
9 111914
11.2%
3 111422
11.1%
7 111274
11.1%
1 111150
11.1%
4 111104
11.1%
6 111098
11.1%
2 110782
11.1%
8 110747
11.1%
5 110509
11.1%
ValueCountFrequency (%)
9 3381
11.3%
2 3358
11.2%
1 3353
11.2%
7 3331
11.1%
8 3327
11.1%
3 3325
11.1%
6 3320
11.1%
5 3309
11.0%
4 3296
11.0%
ValueCountFrequency (%)
1 111150
11.1%
2 110782
11.1%
3 111422
11.1%
4 111104
11.1%
5 110509
11.1%
ValueCountFrequency (%)
1 3353
11.2%
2 3358
11.2%
3 3325
11.1%
4 3296
11.0%
5 3309
11.0%
ValueCountFrequency (%)
1 3353
0.3%
2 3358
0.3%
3 3325
0.3%
4 3296
0.3%
5 3309
0.3%
ValueCountFrequency (%)
1 111150
370.5%
2 110782
369.3%
3 111422
371.4%
4 111104
370.3%
5 110509
368.4%

unit_price
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9989625897
Distinct (%)10.0%86.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500.2613169498.339276
 Full DatasetSimple Random Sample
Minimum11
Maximum1000999.99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:02.052383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile50.7250.998
Q1250.31247.0425
median500.41497
Q3750.16750.3625
95-th percentile949.91949.8905
Maximum1000999.99
Range999998.99
Interquartile range (IQR)499.85503.32

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288.4628596288.7142285
Coefficient of variation (CV)0.57662435590.579352747
Kurtosis-1.20144233-1.209366086
Mean500.2613169498.339276
Median Absolute Deviation (MAD)249.93251.795
Skewness-1.097330655 × 10-50.01338979576
Sum500261316.914950178.28
Variance83210.8213983355.90573
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:02.284573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
226.51 28
 
< 0.1%
450.02 26
 
< 0.1%
591.8 25
 
< 0.1%
921.47 25
 
< 0.1%
354.83 25
 
< 0.1%
49.69 25
 
< 0.1%
111.41 24
 
< 0.1%
954.1 24
 
< 0.1%
619.19 24
 
< 0.1%
845.21 24
 
< 0.1%
Other values (99886) 999750
> 99.9%
ValueCountFrequency (%)
680.14 4
 
< 0.1%
236.54 4
 
< 0.1%
837.2 4
 
< 0.1%
677.76 4
 
< 0.1%
108.44 4
 
< 0.1%
800.72 4
 
< 0.1%
732.05 4
 
< 0.1%
926.62 4
 
< 0.1%
472.22 4
 
< 0.1%
410.82 4
 
< 0.1%
Other values (25887) 29960
99.9%
ValueCountFrequency (%)
1 7
< 0.1%
1.01 9
< 0.1%
1.02 11
< 0.1%
1.03 8
< 0.1%
1.04 17
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
1.02 1
< 0.1%
1.04 1
< 0.1%
1.11 1
< 0.1%
1.12 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
1.02 1
< 0.1%
1.04 1
< 0.1%
1.11 1
< 0.1%
1.12 1
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
1.01 9
< 0.1%
1.02 11
< 0.1%
1.03 8
< 0.1%
1.04 17
0.1%

discount_applied
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.249910490.248603
 Full DatasetSimple Random Sample
Minimum00
Maximum0.50.5
Zeros9967308
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:02.492018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile0.030.02
Q10.130.12
median0.250.25
Q30.370.37
95-th percentile0.470.47
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.240.25

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation0.14432790830.1445862207
Coefficient of variation (CV)0.57751840790.5815948349
Kurtosis-1.19713108-1.197719107
Mean0.249910490.248603
Median Absolute Deviation (MAD)0.120.13
Skewness0.00026409763360.00580058458
Sum249910.497458.09
Variance0.020830545120.02090517523
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:02.690749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.19 20302
 
2.0%
0.06 20213
 
2.0%
0.34 20211
 
2.0%
0.03 20207
 
2.0%
0.05 20207
 
2.0%
0.21 20199
 
2.0%
0.29 20155
 
2.0%
0.07 20153
 
2.0%
0.43 20145
 
2.0%
0.18 20111
 
2.0%
Other values (41) 798097
79.8%
ValueCountFrequency (%)
0.01 647
 
2.2%
0.2 637
 
2.1%
0.1 633
 
2.1%
0.3 630
 
2.1%
0.05 630
 
2.1%
0.4 628
 
2.1%
0.37 627
 
2.1%
0.19 627
 
2.1%
0.35 625
 
2.1%
0.25 624
 
2.1%
Other values (41) 23692
79.0%
ValueCountFrequency (%)
0 9967
1.0%
0.01 20018
2.0%
0.02 19788
2.0%
0.03 20207
2.0%
0.04 19947
2.0%
ValueCountFrequency (%)
0 308
1.0%
0.01 647
2.2%
0.02 606
2.0%
0.03 622
2.1%
0.04 606
2.0%
ValueCountFrequency (%)
0 308
< 0.1%
0.01 647
0.1%
0.02 606
0.1%
0.03 622
0.1%
0.04 606
0.1%
ValueCountFrequency (%)
0 9967
33.2%
0.01 20018
66.7%
0.02 19788
66.0%
0.03 20207
67.4%
0.04 19947
66.5%

payment_method
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:02.925739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1414
Median length1111
Mean length9.7519359.792266667
Min length44

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters9751935293768
Distinct characters1919
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowCredit CardCash
2nd rowCredit CardCash
3rd rowDebit CardMobile Payment
4th rowCredit CardDebit Card
5th rowMobile PaymentCash
ValueCountFrequency (%)
card 500200
28.6%
credit 250435
14.3%
mobile 250030
14.3%
payment 250030
14.3%
cash 249770
14.3%
debit 249765
14.3%
ValueCountFrequency (%)
card 15023
28.5%
mobile 7607
14.5%
payment 7607
14.5%
credit 7560
14.4%
debit 7463
14.2%
cash 7370
14.0%
2025-06-06T01:55:03.285146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30237
10.3%
a 30000
10.2%
C 29953
10.2%
t 22630
 
7.7%
i 22630
 
7.7%
22630
 
7.7%
d 22583
 
7.7%
r 22583
 
7.7%
b 15070
 
5.1%
o 7607
 
2.6%
Other values (9) 67845
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 293768
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30237
10.3%
a 30000
10.2%
C 29953
10.2%
t 22630
 
7.7%
i 22630
 
7.7%
22630
 
7.7%
d 22583
 
7.7%
r 22583
 
7.7%
b 15070
 
5.1%
o 7607
 
2.6%
Other values (9) 67845
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 293768
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30237
10.3%
a 30000
10.2%
C 29953
10.2%
t 22630
 
7.7%
i 22630
 
7.7%
22630
 
7.7%
d 22583
 
7.7%
r 22583
 
7.7%
b 15070
 
5.1%
o 7607
 
2.6%
Other values (9) 67845
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 293768
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30237
10.3%
a 30000
10.2%
C 29953
10.2%
t 22630
 
7.7%
i 22630
 
7.7%
22630
 
7.7%
d 22583
 
7.7%
r 22583
 
7.7%
b 15070
 
5.1%
o 7607
 
2.6%
Other values (9) 67845
23.1%

store_location
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:03.473864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1010
Median length1010
Mean length1010
Min length1010

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters10000000300000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowLocation ALocation D
2nd rowLocation CLocation D
3rd rowLocation ALocation A
4th rowLocation ALocation A
5th rowLocation CLocation A
ValueCountFrequency (%)
location 1000000
50.0%
c 250336
 
12.5%
b 250280
 
12.5%
a 250150
 
12.5%
d 249234
 
12.5%
ValueCountFrequency (%)
location 30000
50.0%
d 7539
 
12.6%
c 7496
 
12.5%
a 7491
 
12.5%
b 7474
 
12.5%
2025-06-06T01:55:03.746571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
D 7539
 
2.5%
C 7496
 
2.5%
Other values (2) 14965
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
D 7539
 
2.5%
C 7496
 
2.5%
Other values (2) 14965
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
D 7539
 
2.5%
C 7496
 
2.5%
Other values (2) 14965
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
D 7539
 
2.5%
C 7496
 
2.5%
Other values (2) 14965
 
5.0%

transaction_hour
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct2424
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean11.50519311.47983333
 Full DatasetSimple Random Sample
Minimum00
Maximum2323
Zeros417561259
Zeros (%)4.2%4.2%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:03.855896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile11
Q156
median1211
Q31817
95-th percentile2222
Maximum2323
Range2323
Interquartile range (IQR)1311

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation6.9244597616.909875893
Coefficient of variation (CV)0.60185515890.6019143042
Kurtosis-1.205305317-1.199746514
Mean11.50519311.47983333
Median Absolute Deviation (MAD)66
Skewness-0.0015312977070.006555929836
Sum11505193344395
Variance47.9481429847.74638485
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:03.983648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
5 42166
 
4.2%
14 42161
 
4.2%
18 41872
 
4.2%
20 41812
 
4.2%
3 41780
 
4.2%
21 41778
 
4.2%
4 41756
 
4.2%
0 41756
 
4.2%
23 41750
 
4.2%
19 41707
 
4.2%
Other values (14) 581462
58.1%
ValueCountFrequency (%)
7 1296
 
4.3%
8 1294
 
4.3%
11 1289
 
4.3%
20 1279
 
4.3%
16 1279
 
4.3%
3 1273
 
4.2%
10 1270
 
4.2%
14 1269
 
4.2%
5 1266
 
4.2%
15 1260
 
4.2%
Other values (14) 17225
57.4%
ValueCountFrequency (%)
0 41756
4.2%
1 41637
4.2%
2 41388
4.1%
3 41780
4.2%
4 41756
4.2%
ValueCountFrequency (%)
0 1259
4.2%
1 1232
4.1%
2 1236
4.1%
3 1273
4.2%
4 1195
4.0%
ValueCountFrequency (%)
0 1259
0.1%
1 1232
0.1%
2 1236
0.1%
3 1273
0.1%
4 1195
0.1%
ValueCountFrequency (%)
0 41756
139.2%
1 41637
138.8%
2 41388
138.0%
3 41780
139.3%
4 41756
139.2%

day_of_week
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct77
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:04.275522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length99
Median length88
Mean length7.1410757.140866667
Min length66

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters7141075214226
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowWednesdaySaturday
2nd rowFridaySaturday
3rd rowSaturdaySaturday
4th rowFridayTuesday
5th rowMondayTuesday
ValueCountFrequency (%)
tuesday 143452
14.3%
friday 143067
14.3%
thursday 142930
14.3%
sunday 142875
14.3%
monday 142855
14.3%
saturday 142700
14.3%
wednesday 142121
14.2%
ValueCountFrequency (%)
saturday 4415
14.7%
tuesday 4359
14.5%
monday 4305
14.3%
thursday 4283
14.3%
friday 4263
14.2%
sunday 4218
14.1%
wednesday 4157
13.9%
2025-06-06T01:55:04.645661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34415
16.1%
d 34157
15.9%
y 30000
14.0%
u 17275
8.1%
r 12961
 
6.1%
s 12799
 
6.0%
n 12680
 
5.9%
e 12673
 
5.9%
T 8642
 
4.0%
S 8633
 
4.0%
Other values (7) 29991
14.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214226
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34415
16.1%
d 34157
15.9%
y 30000
14.0%
u 17275
8.1%
r 12961
 
6.1%
s 12799
 
6.0%
n 12680
 
5.9%
e 12673
 
5.9%
T 8642
 
4.0%
S 8633
 
4.0%
Other values (7) 29991
14.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214226
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34415
16.1%
d 34157
15.9%
y 30000
14.0%
u 17275
8.1%
r 12961
 
6.1%
s 12799
 
6.0%
n 12680
 
5.9%
e 12673
 
5.9%
T 8642
 
4.0%
S 8633
 
4.0%
Other values (7) 29991
14.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214226
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34415
16.1%
d 34157
15.9%
y 30000
14.0%
u 17275
8.1%
r 12961
 
6.1%
s 12799
 
6.0%
n 12680
 
5.9%
e 12673
 
5.9%
T 8642
 
4.0%
S 8633
 
4.0%
Other values (7) 29991
14.0%

week_of_year
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct5252
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean26.50369126.35216667
 Full DatasetSimple Random Sample
Minimum11
Maximum5252
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:04.816406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile33
Q11413
median2726
Q33939
95-th percentile5050
Maximum5252
Range5151
Interquartile range (IQR)2526

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation15.0051651615.00926118
Coefficient of variation (CV)0.5661537920.5695645968
Kurtosis-1.199199248-1.202720439
Mean26.50369126.35216667
Median Absolute Deviation (MAD)1313
Skewness-0.00059099783510.01246505008
Sum26503691790565
Variance225.1549815225.2779212
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:05.017035image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 19588
 
2.0%
19 19507
 
2.0%
51 19447
 
1.9%
26 19425
 
1.9%
1 19399
 
1.9%
25 19386
 
1.9%
21 19371
 
1.9%
44 19356
 
1.9%
16 19348
 
1.9%
9 19340
 
1.9%
Other values (42) 805833
80.6%
ValueCountFrequency (%)
27 630
 
2.1%
6 623
 
2.1%
41 618
 
2.1%
26 613
 
2.0%
18 608
 
2.0%
51 602
 
2.0%
13 601
 
2.0%
15 600
 
2.0%
43 599
 
2.0%
8 598
 
2.0%
Other values (42) 23908
79.7%
ValueCountFrequency (%)
1 19399
1.9%
2 19179
1.9%
3 19150
1.9%
4 19137
1.9%
5 19328
1.9%
ValueCountFrequency (%)
1 586
2.0%
2 563
1.9%
3 596
2.0%
4 586
2.0%
5 586
2.0%
ValueCountFrequency (%)
1 586
0.1%
2 563
0.1%
3 596
0.1%
4 586
0.1%
5 586
0.1%
ValueCountFrequency (%)
1 19399
64.7%
2 19179
63.9%
3 19150
63.8%
4 19137
63.8%
5 19328
64.4%

month_of_year
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct1212
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6.4974676.491633333
 Full DatasetSimple Random Sample
Minimum11
Maximum1212
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:05.156657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile11
Q133
median76
Q31010
95-th percentile1212
Maximum1212
Range1111
Interquartile range (IQR)77

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation3.4552119363.467794331
Coefficient of variation (CV)0.5317782970.5341944242
Kurtosis-1.21903855-1.231347126
Mean6.4974676.491633333
Median Absolute Deviation (MAD)33
Skewness0.00038204364360.0001544758843
Sum6497467194749
Variance11.9384895212.02559752
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:05.274489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 83951
8.4%
11 83645
8.4%
1 83624
8.4%
7 83475
8.3%
12 83353
8.3%
9 83328
8.3%
3 83244
8.3%
5 83135
8.3%
10 83113
8.3%
8 83093
8.3%
Other values (2) 166039
16.6%
ValueCountFrequency (%)
2 2596
8.7%
10 2559
8.5%
8 2540
8.5%
3 2525
8.4%
12 2521
8.4%
1 2519
8.4%
9 2480
8.3%
4 2477
8.3%
6 2476
8.3%
11 2474
8.2%
Other values (2) 4833
16.1%
ValueCountFrequency (%)
1 83624
8.4%
2 83951
8.4%
3 83244
8.3%
4 83091
8.3%
5 83135
8.3%
ValueCountFrequency (%)
1 2519
8.4%
2 2596
8.7%
3 2525
8.4%
4 2477
8.3%
5 2414
8.0%
ValueCountFrequency (%)
1 2519
0.3%
2 2596
0.3%
3 2525
0.3%
4 2477
0.2%
5 2414
0.2%
ValueCountFrequency (%)
1 83624
278.7%
2 83951
279.8%
3 83244
277.5%
4 83091
277.0%
5 83135
277.1%

avg_purchase_value
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct4900122484
Distinct (%)4.9%74.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean254.8864443254.2088407
 Full DatasetSimple Random Sample
Minimum1010
Maximum500499.96
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:05.470272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1010
5-th percentile34.433.5685
Q1132.22131.6775
median254.93253.515
Q3377.35378.2525
95-th percentile475.56475.3905
Maximum500499.96
Range490489.96
Interquartile range (IQR)245.13246.575

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation141.4949233141.7735923
Coefficient of variation (CV)0.55512926040.5577051998
Kurtosis-1.200170422-1.204034232
Mean254.8864443254.2088407
Median Absolute Deviation (MAD)122.57123.37
Skewness0.00037628335860.008232581978
Sum254886444.37626265.22
Variance20020.8133320099.75147
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:05.999048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76.54 41
 
< 0.1%
482.75 41
 
< 0.1%
372.04 40
 
< 0.1%
397.45 39
 
< 0.1%
246.87 39
 
< 0.1%
60.53 38
 
< 0.1%
278.34 38
 
< 0.1%
315.26 38
 
< 0.1%
165.81 38
 
< 0.1%
492.47 38
 
< 0.1%
Other values (48991) 999610
> 99.9%
ValueCountFrequency (%)
151.48 6
 
< 0.1%
68.49 6
 
< 0.1%
497.15 5
 
< 0.1%
217.3 5
 
< 0.1%
97.73 5
 
< 0.1%
271.98 5
 
< 0.1%
309.43 5
 
< 0.1%
69 5
 
< 0.1%
41.4 5
 
< 0.1%
496.99 5
 
< 0.1%
Other values (22474) 29948
99.8%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 23
< 0.1%
10.02 29
< 0.1%
10.03 17
< 0.1%
10.04 21
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.03 2
< 0.1%
10.05 2
< 0.1%
10.08 2
< 0.1%
10.1 1
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.03 2
< 0.1%
10.05 2
< 0.1%
10.08 2
< 0.1%
10.1 1
< 0.1%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 23
0.1%
10.02 29
0.1%
10.03 17
0.1%
10.04 21
0.1%

purchase_frequency
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:06.267245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length77
Median length66
Mean length6.0003995.999766667
Min length55

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters6000399179993
Distinct characters1515
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowWeeklyWeekly
2nd rowDailyMonthly
3rd rowWeeklyWeekly
4th rowWeeklyWeekly
5th rowYearlyDaily
ValueCountFrequency (%)
yearly 250767
25.1%
monthly 249932
25.0%
weekly 249768
25.0%
daily 249533
25.0%
ValueCountFrequency (%)
yearly 7524
25.1%
weekly 7519
25.1%
daily 7482
24.9%
monthly 7475
24.9%
2025-06-06T01:55:06.682663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22562
12.5%
a 15006
8.3%
Y 7524
 
4.2%
r 7524
 
4.2%
W 7519
 
4.2%
k 7519
 
4.2%
D 7482
 
4.2%
i 7482
 
4.2%
Other values (5) 37375
20.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179993
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22562
12.5%
a 15006
8.3%
Y 7524
 
4.2%
r 7524
 
4.2%
W 7519
 
4.2%
k 7519
 
4.2%
D 7482
 
4.2%
i 7482
 
4.2%
Other values (5) 37375
20.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179993
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22562
12.5%
a 15006
8.3%
Y 7524
 
4.2%
r 7524
 
4.2%
W 7519
 
4.2%
k 7519
 
4.2%
D 7482
 
4.2%
i 7482
 
4.2%
Other values (5) 37375
20.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179993
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22562
12.5%
a 15006
8.3%
Y 7524
 
4.2%
r 7524
 
4.2%
W 7519
 
4.2%
k 7519
 
4.2%
D 7482
 
4.2%
i 7482
 
4.2%
Other values (5) 37375
20.8%

last_purchase_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct98424229984
Distinct (%)98.4%99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:07.662278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique96865629968 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSimple Random Sample
1st row2021-09-11 04:22:382021-03-22 06:11:14
2nd row2021-05-16 12:01:162021-05-25 01:33:35
3rd row2021-02-07 16:47:482021-04-08 07:24:34
4th row2021-12-30 23:48:262021-05-01 08:25:43
5th row2021-11-02 11:48:252021-10-17 16:57:36
ValueCountFrequency (%)
2021-01-02 2870
 
0.1%
2021-05-14 2866
 
0.1%
2021-12-25 2860
 
0.1%
2021-01-17 2860
 
0.1%
2021-10-17 2856
 
0.1%
2021-01-26 2856
 
0.1%
2021-08-16 2854
 
0.1%
2021-05-05 2852
 
0.1%
2021-10-16 2850
 
0.1%
2021-09-17 2849
 
0.1%
Other values (86754) 1971427
98.6%
ValueCountFrequency (%)
2021-12-30 108
 
0.2%
2021-06-20 104
 
0.2%
2021-06-01 104
 
0.2%
2021-12-16 102
 
0.2%
2021-09-10 102
 
0.2%
2021-07-01 101
 
0.2%
2021-12-29 101
 
0.2%
2021-10-17 100
 
0.2%
2021-06-15 100
 
0.2%
2021-01-25 100
 
0.2%
Other values (25753) 58978
98.3%
2025-06-06T01:55:08.796376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102714
18.0%
0 98606
17.3%
1 88392
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26635
 
4.7%
5 24202
 
4.2%
4 23836
 
4.2%
7 13969
 
2.5%
Other values (3) 41646
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102714
18.0%
0 98606
17.3%
1 88392
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26635
 
4.7%
5 24202
 
4.2%
4 23836
 
4.2%
7 13969
 
2.5%
Other values (3) 41646
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102714
18.0%
0 98606
17.3%
1 88392
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26635
 
4.7%
5 24202
 
4.2%
4 23836
 
4.2%
7 13969
 
2.5%
Other values (3) 41646
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102714
18.0%
0 98606
17.3%
1 88392
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26635
 
4.7%
5 24202
 
4.2%
4 23836
 
4.2%
7 13969
 
2.5%
Other values (3) 41646
7.3%

avg_discount_used
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.250010090.251375
 Full DatasetSimple Random Sample
Minimum00
Maximum0.50.5
Zeros10010302
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:09.077047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile0.030.03
Q10.130.13
median0.250.25
Q30.380.38
95-th percentile0.470.48
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.250.25

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation0.14438256280.1443910004
Coefficient of variation (CV)0.57750694310.5744047754
Kurtosis-1.19810725-1.197196779
Mean0.250010090.251375
Median Absolute Deviation (MAD)0.120.13
Skewness0.0002818589406-0.01244620285
Sum250010.097541.25
Variance0.020846324440.020848761
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:09.435851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.39 20194
 
2.0%
0.15 20188
 
2.0%
0.08 20140
 
2.0%
0.21 20138
 
2.0%
0.34 20131
 
2.0%
0.47 20125
 
2.0%
0.05 20124
 
2.0%
0.16 20123
 
2.0%
0.46 20109
 
2.0%
0.32 20093
 
2.0%
Other values (41) 798635
79.9%
ValueCountFrequency (%)
0.39 639
 
2.1%
0.44 634
 
2.1%
0.42 631
 
2.1%
0.33 630
 
2.1%
0.25 629
 
2.1%
0.28 629
 
2.1%
0.1 626
 
2.1%
0.15 626
 
2.1%
0.48 621
 
2.1%
0.06 619
 
2.1%
Other values (41) 23716
79.1%
ValueCountFrequency (%)
0 10010
1.0%
0.01 19893
2.0%
0.02 19951
2.0%
0.03 19949
2.0%
0.04 20004
2.0%
ValueCountFrequency (%)
0 302
1.0%
0.01 578
1.9%
0.02 555
1.8%
0.03 597
2.0%
0.04 598
2.0%
ValueCountFrequency (%)
0 302
< 0.1%
0.01 578
0.1%
0.02 555
0.1%
0.03 597
0.1%
0.04 598
0.1%
ValueCountFrequency (%)
0 10010
33.4%
0.01 19893
66.3%
0.02 19951
66.5%
0.03 19949
66.5%
0.04 20004
66.7%

preferred_store
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:09.812503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1010
Median length1010
Mean length1010
Min length1010

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters10000000300000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowLocation ALocation D
2nd rowLocation CLocation B
3rd rowLocation BLocation C
4th rowLocation BLocation A
5th rowLocation BLocation C
ValueCountFrequency (%)
location 1000000
50.0%
b 250262
 
12.5%
d 250007
 
12.5%
a 249949
 
12.5%
c 249782
 
12.5%
ValueCountFrequency (%)
location 30000
50.0%
c 7545
 
12.6%
b 7537
 
12.6%
a 7467
 
12.4%
d 7451
 
12.4%
2025-06-06T01:55:10.255639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
C 7545
 
2.5%
B 7537
 
2.5%
Other values (2) 14918
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
C 7545
 
2.5%
B 7537
 
2.5%
Other values (2) 14918
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
C 7545
 
2.5%
B 7537
 
2.5%
Other values (2) 14918
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
C 7545
 
2.5%
B 7537
 
2.5%
Other values (2) 14918
 
5.0%

online_purchases
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.44601849.45993333
 Full DatasetSimple Random Sample
Minimum00
Maximum9999
Zeros9997298
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:10.495213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile44
Q12424
median4950
Q37474
95-th percentile9495
Maximum9999
Range9999
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.8614391328.95485004
Coefficient of variation (CV)0.58369592340.5854203208
Kurtosis-1.200754846-1.197307599
Mean49.44601849.45993333
Median Absolute Deviation (MAD)2525
Skewness0.00143421854-0.003460787705
Sum494460181483798
Variance832.9826689838.3833408
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:10.798946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 10324
 
1.0%
28 10269
 
1.0%
40 10198
 
1.0%
67 10151
 
1.0%
76 10150
 
1.0%
61 10150
 
1.0%
52 10140
 
1.0%
88 10134
 
1.0%
43 10133
 
1.0%
45 10132
 
1.0%
Other values (90) 898219
89.8%
ValueCountFrequency (%)
41 339
 
1.1%
57 334
 
1.1%
75 334
 
1.1%
1 329
 
1.1%
11 328
 
1.1%
21 327
 
1.1%
8 325
 
1.1%
39 325
 
1.1%
82 325
 
1.1%
98 324
 
1.1%
Other values (90) 26710
89.0%
ValueCountFrequency (%)
0 9997
1.0%
1 10023
1.0%
2 9792
1.0%
3 10091
1.0%
4 10324
1.0%
ValueCountFrequency (%)
0 298
1.0%
1 329
1.1%
2 322
1.1%
3 318
1.1%
4 324
1.1%
ValueCountFrequency (%)
0 298
< 0.1%
1 329
< 0.1%
2 322
< 0.1%
3 318
< 0.1%
4 324
< 0.1%
ValueCountFrequency (%)
0 9997
33.3%
1 10023
33.4%
2 9792
32.6%
3 10091
33.6%
4 10324
34.4%

in_store_purchases
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.48448649.4573
 Full DatasetSimple Random Sample
Minimum00
Maximum9999
Zeros10016299
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:11.095939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile55
Q12425
median4949
Q37574
95-th percentile9595
Maximum9999
Range9999
Interquartile range (IQR)5149

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.8827117428.7980547
Coefficient of variation (CV)0.58367205720.5822811738
Kurtosis-1.20140369-1.193695209
Mean49.48448649.4573
Median Absolute Deviation (MAD)2525
Skewness0.001590435670.009739166877
Sum494844861483719
Variance834.2110375829.3279543
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:11.395022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 10264
 
1.0%
30 10186
 
1.0%
86 10183
 
1.0%
10 10180
 
1.0%
14 10171
 
1.0%
7 10166
 
1.0%
13 10164
 
1.0%
50 10151
 
1.0%
67 10141
 
1.0%
91 10131
 
1.0%
Other values (90) 898263
89.8%
ValueCountFrequency (%)
45 341
 
1.1%
27 337
 
1.1%
75 335
 
1.1%
32 334
 
1.1%
33 333
 
1.1%
18 331
 
1.1%
97 325
 
1.1%
63 325
 
1.1%
12 325
 
1.1%
51 323
 
1.1%
Other values (90) 26691
89.0%
ValueCountFrequency (%)
0 10016
1.0%
1 9978
1.0%
2 9953
1.0%
3 9965
1.0%
4 9926
1.0%
ValueCountFrequency (%)
0 299
1.0%
1 289
1.0%
2 309
1.0%
3 291
1.0%
4 272
0.9%
ValueCountFrequency (%)
0 299
< 0.1%
1 289
< 0.1%
2 309
< 0.1%
3 291
< 0.1%
4 272
< 0.1%
ValueCountFrequency (%)
0 10016
33.4%
1 9978
33.3%
2 9953
33.2%
3 9965
33.2%
4 9926
33.1%

avg_items_per_transaction
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct901901
Distinct (%)0.1%3.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.503121875.502303
 Full DatasetSimple Random Sample
Minimum11
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:11.739589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile1.451.46
Q13.263.24
median5.55.5
Q37.757.74
95-th percentile9.559.56
Maximum1010
Range99
Interquartile range (IQR)4.494.5

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.5976612752.600037786
Coefficient of variation (CV)0.47203411730.472536279
Kurtosis-1.199082145-1.201673737
Mean5.503121875.502303
Median Absolute Deviation (MAD)2.252.25
Skewness-4.461054903 × 10-50.0006816036718
Sum5503121.87165069.09
Variance6.7478440976.760196486
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:12.066544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.49 1205
 
0.1%
5 1198
 
0.1%
3.94 1197
 
0.1%
6.41 1196
 
0.1%
2.82 1193
 
0.1%
8.41 1192
 
0.1%
9.69 1192
 
0.1%
4.29 1190
 
0.1%
4.35 1188
 
0.1%
6.14 1188
 
0.1%
Other values (891) 988061
98.8%
ValueCountFrequency (%)
3.65 54
 
0.2%
1.5 53
 
0.2%
4.73 51
 
0.2%
1.54 50
 
0.2%
1.8 49
 
0.2%
3.32 49
 
0.2%
4.34 48
 
0.2%
2.39 48
 
0.2%
5.93 48
 
0.2%
6.42 47
 
0.2%
Other values (891) 29503
98.3%
ValueCountFrequency (%)
1 514
0.1%
1.01 1135
0.1%
1.02 1105
0.1%
1.03 1122
0.1%
1.04 1067
0.1%
ValueCountFrequency (%)
1 17
0.1%
1.01 33
0.1%
1.02 35
0.1%
1.03 20
0.1%
1.04 37
0.1%
ValueCountFrequency (%)
1 17
< 0.1%
1.01 33
< 0.1%
1.02 35
< 0.1%
1.03 20
< 0.1%
1.04 37
< 0.1%
ValueCountFrequency (%)
1 514
1.7%
1.01 1135
3.8%
1.02 1105
3.7%
1.03 1122
3.7%
1.04 1067
3.6%

avg_transaction_value
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct4900122324
Distinct (%)4.9%74.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean255.1157678256.6698107
 Full DatasetSimple Random Sample
Minimum1010
Maximum500499.98
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:12.393623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1010
5-th percentile34.5235.719
Q1132.51133.1875
median255.23257.275
Q3377.67379.44
95-th percentile475.36476.2705
Maximum500499.98
Range490489.98
Interquartile range (IQR)245.16246.2525

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation141.4300141141.6362806
Coefficient of variation (CV)0.55437582430.5518229051
Kurtosis-1.200885422-1.2059291
Mean255.1157678256.6698107
Median Absolute Deviation (MAD)122.58123.1
Skewness-0.001148163222-0.01336002992
Sum255115767.87700094.32
Variance20002.4488820060.83597
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:12.727502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
362.11 43
 
< 0.1%
157.68 43
 
< 0.1%
86.72 42
 
< 0.1%
303.99 41
 
< 0.1%
193.66 41
 
< 0.1%
112.64 40
 
< 0.1%
342.26 40
 
< 0.1%
454.72 39
 
< 0.1%
64.18 39
 
< 0.1%
280.55 39
 
< 0.1%
Other values (48991) 999593
> 99.9%
ValueCountFrequency (%)
313.35 6
 
< 0.1%
295.85 6
 
< 0.1%
64.18 6
 
< 0.1%
52.31 5
 
< 0.1%
468.17 5
 
< 0.1%
256.12 5
 
< 0.1%
430.08 5
 
< 0.1%
221.08 5
 
< 0.1%
234.56 5
 
< 0.1%
420.51 5
 
< 0.1%
Other values (22314) 29947
99.8%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 18
< 0.1%
10.02 17
< 0.1%
10.03 28
< 0.1%
10.04 24
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.01 1
< 0.1%
10.03 2
< 0.1%
10.08 1
< 0.1%
10.1 2
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.01 1
< 0.1%
10.03 2
< 0.1%
10.08 1
< 0.1%
10.1 2
< 0.1%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 18
0.1%
10.02 17
0.1%
10.03 28
0.1%
10.04 24
0.1%

total_returned_items
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct1010
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.4981424.464266667
 Full DatasetSimple Random Sample
Minimum00
Maximum99
Zeros1000603135
Zeros (%)10.0%10.4%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:12.929048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile00
Q122
median44
Q377
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)55

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.8728050412.882764901
Coefficient of variation (CV)0.63866481770.6457420929
Kurtosis-1.225109848-1.231347532
Mean4.4981424.464266667
Median Absolute Deviation (MAD)33
Skewness0.00076922547280.009257208818
Sum4498142133928
Variance8.2530088018.310333473
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:13.030146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 100298
10.0%
7 100190
10.0%
3 100119
10.0%
0 100060
10.0%
6 100004
10.0%
2 99991
10.0%
9 99942
10.0%
8 99838
10.0%
4 99821
10.0%
5 99737
10.0%
ValueCountFrequency (%)
0 3135
10.4%
1 3062
10.2%
5 3009
10.0%
3 3006
10.0%
7 2997
10.0%
6 2970
9.9%
8 2968
9.9%
2 2961
9.9%
9 2954
9.8%
4 2938
9.8%
ValueCountFrequency (%)
0 100060
10.0%
1 100298
10.0%
2 99991
10.0%
3 100119
10.0%
4 99821
10.0%
ValueCountFrequency (%)
0 3135
10.4%
1 3062
10.2%
2 2961
9.9%
3 3006
10.0%
4 2938
9.8%
ValueCountFrequency (%)
0 3135
0.3%
1 3062
0.3%
2 2961
0.3%
3 3006
0.3%
4 2938
0.3%
ValueCountFrequency (%)
0 100060
333.5%
1 100298
334.3%
2 99991
333.3%
3 100119
333.7%
4 99821
332.7%

total_returned_value
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9999925869
Distinct (%)10.0%86.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500.3878374500.9436267
 Full DatasetSimple Random Sample
Minimum00.02
Maximum1000999.99
Zeros40
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:13.198752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00.02
5-th percentile5049.809
Q1250.63250.02
median500.4501.025
Q3750.39751.0975
95-th percentile950.22951.2205
Maximum1000999.99
Range1000999.97
Interquartile range (IQR)499.76501.0775

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288.7174763289.3080814
Coefficient of variation (CV)0.57698739810.5775262246
Kurtosis-1.199754459-1.20327929
Mean500.3878374500.9436267
Median Absolute Deviation (MAD)249.89250.465
Skewness-0.001264828821-0.004269899217
Sum500387837.415028308.8
Variance83357.7811583699.16599
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:13.455424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160.66 28
 
< 0.1%
467.66 26
 
< 0.1%
188.3 26
 
< 0.1%
488.88 25
 
< 0.1%
544.94 25
 
< 0.1%
651.87 25
 
< 0.1%
981.42 25
 
< 0.1%
330.91 25
 
< 0.1%
676.05 25
 
< 0.1%
227.59 25
 
< 0.1%
Other values (99989) 999745
> 99.9%
ValueCountFrequency (%)
998.47 4
 
< 0.1%
814.15 4
 
< 0.1%
162.92 4
 
< 0.1%
570.47 4
 
< 0.1%
947.76 4
 
< 0.1%
311.15 4
 
< 0.1%
73.26 4
 
< 0.1%
192.05 4
 
< 0.1%
48.53 4
 
< 0.1%
247.49 4
 
< 0.1%
Other values (25859) 29960
99.9%
ValueCountFrequency (%)
0 4
 
< 0.1%
0.01 13
< 0.1%
0.02 12
< 0.1%
0.03 11
< 0.1%
0.04 7
< 0.1%
ValueCountFrequency (%)
0.02 2
< 0.1%
0.1 1
< 0.1%
0.12 1
< 0.1%
0.19 1
< 0.1%
0.24 1
< 0.1%
ValueCountFrequency (%)
0.02 2
< 0.1%
0.1 1
< 0.1%
0.12 1
< 0.1%
0.19 1
< 0.1%
0.24 1
< 0.1%
ValueCountFrequency (%)
0 4
 
< 0.1%
0.01 13
< 0.1%
0.02 12
< 0.1%
0.03 11
< 0.1%
0.04 7
< 0.1%

total_sales
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct62925429566
Distinct (%)62.9%98.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5056.0597655074.836803
 Full DatasetSimple Random Sample
Minimum100.01100.28
Maximum9999.989999.79
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:13.671789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum100.01100.28
5-th percentile595.7095612.2615
Q12577.86752603.295
median5059.6955090.995
Q37534.80257536.325
95-th percentile9507.969484.8055
Maximum9999.989999.79
Range9899.979899.51
Interquartile range (IQR)4956.9354933.03

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2859.1000582850.353674
Coefficient of variation (CV)0.56547987770.5616641056
Kurtosis-1.201132214-1.1989154
Mean5056.0597655074.836803
Median Absolute Deviation (MAD)2478.3652463.705
Skewness-0.002792355347-0.01444744546
Sum5056059765152245104.1
Variance8174453.148124516.067
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:13.894206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9263.29 8
 
< 0.1%
1070.51 8
 
< 0.1%
8973.11 8
 
< 0.1%
7882.97 8
 
< 0.1%
630.03 8
 
< 0.1%
8669.59 8
 
< 0.1%
8191.02 8
 
< 0.1%
2558.91 8
 
< 0.1%
5572.95 8
 
< 0.1%
8266.95 8
 
< 0.1%
Other values (629244) 999920
> 99.9%
ValueCountFrequency (%)
7648.63 3
 
< 0.1%
4603.16 3
 
< 0.1%
318.97 3
 
< 0.1%
5631.28 3
 
< 0.1%
9297.5 3
 
< 0.1%
663.71 2
 
< 0.1%
8685.83 2
 
< 0.1%
3507.72 2
 
< 0.1%
7211.09 2
 
< 0.1%
5902.63 2
 
< 0.1%
Other values (29556) 29975
99.9%
ValueCountFrequency (%)
100.01 2
< 0.1%
100.02 2
< 0.1%
100.04 2
< 0.1%
100.05 2
< 0.1%
100.06 3
< 0.1%
ValueCountFrequency (%)
100.28 1
< 0.1%
100.67 1
< 0.1%
100.69 1
< 0.1%
101.29 1
< 0.1%
101.66 1
< 0.1%
ValueCountFrequency (%)
100.28 1
< 0.1%
100.67 1
< 0.1%
100.69 1
< 0.1%
101.29 1
< 0.1%
101.66 1
< 0.1%
ValueCountFrequency (%)
100.01 2
< 0.1%
100.02 2
< 0.1%
100.04 2
< 0.1%
100.05 2
< 0.1%
100.06 3
< 0.1%

total_transactions
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9999
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.98738649.9852
 Full DatasetSimple Random Sample
Minimum11
Maximum9999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:14.553493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile55
Q12525
median5050
Q37575
95-th percentile9594
Maximum9999
Range9898
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.5716889528.62659888
Coefficient of variation (CV)0.57157797660.5727014973
Kurtosis-1.200697232-1.204789583
Mean49.98738649.9852
Median Absolute Deviation (MAD)2525
Skewness6.496950968 × 10-5-0.004753357477
Sum499873861499556
Variance816.3414092819.4821637
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:14.780864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93 10385
 
1.0%
24 10328
 
1.0%
61 10316
 
1.0%
70 10306
 
1.0%
49 10290
 
1.0%
14 10280
 
1.0%
83 10278
 
1.0%
27 10251
 
1.0%
16 10247
 
1.0%
75 10245
 
1.0%
Other values (89) 897074
89.7%
ValueCountFrequency (%)
53 350
 
1.2%
39 348
 
1.2%
46 342
 
1.1%
6 341
 
1.1%
84 341
 
1.1%
3 339
 
1.1%
14 337
 
1.1%
61 327
 
1.1%
56 325
 
1.1%
71 323
 
1.1%
Other values (89) 26627
88.8%
ValueCountFrequency (%)
1 10053
1.0%
2 10174
1.0%
3 10113
1.0%
4 10133
1.0%
5 10140
1.0%
ValueCountFrequency (%)
1 314
1.0%
2 282
0.9%
3 339
1.1%
4 295
1.0%
5 312
1.0%
ValueCountFrequency (%)
1 314
< 0.1%
2 282
< 0.1%
3 339
< 0.1%
4 295
< 0.1%
5 312
< 0.1%
ValueCountFrequency (%)
1 10053
33.5%
2 10174
33.9%
3 10113
33.7%
4 10133
33.8%
5 10140
33.8%

total_items_purchased
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct499499
Distinct (%)< 0.1%1.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean250.042763249.6875333
 Full DatasetSimple Random Sample
Minimum11
Maximum499499
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:14.997541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile2625
Q1125126
median250249
Q3375374
95-th percentile475475
Maximum499499
Range498498
Interquartile range (IQR)250248

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation143.9845462143.9265915
Coefficient of variation (CV)0.57583968620.5764268225
Kurtosis-1.199364571-1.189195838
Mean250.042763249.6875333
Median Absolute Deviation (MAD)125124
Skewness-0.00052895379850.004878498838
Sum2500427637490626
Variance20731.5495420714.86373
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:15.207760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
282 2156
 
0.2%
285 2146
 
0.2%
355 2132
 
0.2%
459 2099
 
0.2%
296 2098
 
0.2%
241 2096
 
0.2%
413 2090
 
0.2%
331 2088
 
0.2%
425 2087
 
0.2%
260 2086
 
0.2%
Other values (489) 978922
97.9%
ValueCountFrequency (%)
294 83
 
0.3%
109 83
 
0.3%
370 81
 
0.3%
223 79
 
0.3%
88 79
 
0.3%
156 78
 
0.3%
454 78
 
0.3%
147 77
 
0.3%
402 77
 
0.3%
224 77
 
0.3%
Other values (489) 29208
97.4%
ValueCountFrequency (%)
1 2005
0.2%
2 2077
0.2%
3 1999
0.2%
4 2019
0.2%
5 1988
0.2%
ValueCountFrequency (%)
1 59
0.2%
2 77
0.3%
3 62
0.2%
4 49
0.2%
5 56
0.2%
ValueCountFrequency (%)
1 59
< 0.1%
2 77
< 0.1%
3 62
< 0.1%
4 49
< 0.1%
5 56
< 0.1%
ValueCountFrequency (%)
1 2005
6.7%
2 2077
6.9%
3 1999
6.7%
4 2019
6.7%
5 1988
6.6%

total_discounts_received
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9999525887
Distinct (%)10.0%86.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.6743882499.0057443
 Full DatasetSimple Random Sample
Minimum00.03
Maximum1000999.98
Zeros60
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:15.428066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00.03
5-th percentile50.1650.7575
Q1249.76247.475
median499.51497.23
Q3749.54748.0925
95-th percentile949.66949.392
Maximum1000999.98
Range1000999.95
Interquartile range (IQR)499.78500.6175

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288.5791016288.4654098
Coefficient of variation (CV)0.57753430710.5780803389
Kurtosis-1.200167414-1.203167198
Mean499.6743882499.0057443
Median Absolute Deviation (MAD)249.9250.27
Skewness0.00097450105350.006700621698
Sum499674388.214970172.33
Variance83277.8978683212.29266
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:15.664991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52.87 26
 
< 0.1%
811.21 26
 
< 0.1%
721.58 26
 
< 0.1%
418.88 25
 
< 0.1%
760.97 25
 
< 0.1%
406.5 24
 
< 0.1%
784.58 24
 
< 0.1%
595.87 24
 
< 0.1%
918 24
 
< 0.1%
34.86 24
 
< 0.1%
Other values (99985) 999752
> 99.9%
ValueCountFrequency (%)
940.14 4
 
< 0.1%
776.49 4
 
< 0.1%
119.88 4
 
< 0.1%
888.26 4
 
< 0.1%
175.56 4
 
< 0.1%
244.64 4
 
< 0.1%
360.68 4
 
< 0.1%
985.34 4
 
< 0.1%
795.35 4
 
< 0.1%
115.4 4
 
< 0.1%
Other values (25877) 29960
99.9%
ValueCountFrequency (%)
0 6
< 0.1%
0.01 13
< 0.1%
0.02 8
< 0.1%
0.03 8
< 0.1%
0.04 6
< 0.1%
ValueCountFrequency (%)
0.03 1
< 0.1%
0.05 1
< 0.1%
0.06 2
< 0.1%
0.3 1
< 0.1%
0.31 1
< 0.1%
ValueCountFrequency (%)
0.03 1
< 0.1%
0.05 1
< 0.1%
0.06 2
< 0.1%
0.3 1
< 0.1%
0.31 1
< 0.1%
ValueCountFrequency (%)
0 6
< 0.1%
0.01 13
< 0.1%
0.02 8
< 0.1%
0.03 8
< 0.1%
0.04 6
< 0.1%

avg_spent_per_category
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9899925866
Distinct (%)9.9%86.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean505.1754779507.0576237
 Full DatasetSimple Random Sample
Minimum1010.06
Maximum10001000
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:15.874561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1010.06
5-th percentile59.4959.0795
Q1257.24258.905
median505.14508.155
Q3753.06757.4725
95-th percentile950.7405952.5725
Maximum10001000
Range990989.94
Interquartile range (IQR)495.82498.5675

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation286.0591784287.0447366
Coefficient of variation (CV)0.5662570550.566098848
Kurtosis-1.201963641-1.208071695
Mean505.1754779507.0576237
Median Absolute Deviation (MAD)247.91249.285
Skewness-0.0002454959133-0.005296010855
Sum505175477.915211728.71
Variance81829.8535582394.68082
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:16.096294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202.69 27
 
< 0.1%
969.16 26
 
< 0.1%
582.24 26
 
< 0.1%
806.1 25
 
< 0.1%
330.74 25
 
< 0.1%
798.54 25
 
< 0.1%
299.29 25
 
< 0.1%
312.38 25
 
< 0.1%
825.53 24
 
< 0.1%
525.28 24
 
< 0.1%
Other values (98989) 999748
> 99.9%
ValueCountFrequency (%)
320.57 5
 
< 0.1%
912.73 5
 
< 0.1%
846.38 5
 
< 0.1%
663.16 4
 
< 0.1%
892.36 4
 
< 0.1%
640.34 4
 
< 0.1%
575.37 4
 
< 0.1%
71.64 4
 
< 0.1%
17.8 4
 
< 0.1%
311.13 4
 
< 0.1%
Other values (25856) 29957
99.9%
ValueCountFrequency (%)
10 4
 
< 0.1%
10.01 8
< 0.1%
10.02 13
< 0.1%
10.03 10
< 0.1%
10.04 13
< 0.1%
ValueCountFrequency (%)
10.06 1
< 0.1%
10.1 1
< 0.1%
10.11 1
< 0.1%
10.12 1
< 0.1%
10.18 1
< 0.1%
ValueCountFrequency (%)
10.06 1
< 0.1%
10.1 1
< 0.1%
10.11 1
< 0.1%
10.12 1
< 0.1%
10.18 1
< 0.1%
ValueCountFrequency (%)
10 4
 
< 0.1%
10.01 8
< 0.1%
10.02 13
< 0.1%
10.03 10
< 0.1%
10.04 13
< 0.1%

max_single_purchase_value
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct9900125907
Distinct (%)9.9%86.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean505.0014045504.536687
 Full DatasetSimple Random Sample
Minimum1010.02
Maximum1000999.99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:16.306094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1010.02
5-th percentile59.360.8095
Q1256.84258.6275
median505.22506.25
Q3753.21749.5475
95-th percentile950.55949.1635
Maximum1000999.99
Range990989.97
Interquartile range (IQR)496.37490.92

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation286.0733241284.1505107
Coefficient of variation (CV)0.56648025450.5631909789
Kurtosis-1.202495075-1.189490667
Mean505.0014045504.536687
Median Absolute Deviation (MAD)248.18245.72
Skewness-0.0008466890807-0.002101584338
Sum505001404.515136100.61
Variance81837.9467780741.5127
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:16.516846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
575.57 28
 
< 0.1%
461.6 26
 
< 0.1%
874.29 25
 
< 0.1%
105.78 25
 
< 0.1%
354.85 25
 
< 0.1%
736.87 25
 
< 0.1%
439.72 25
 
< 0.1%
893.75 24
 
< 0.1%
179.32 24
 
< 0.1%
330.94 24
 
< 0.1%
Other values (98991) 999749
> 99.9%
ValueCountFrequency (%)
831.01 5
 
< 0.1%
459.85 4
 
< 0.1%
537.43 4
 
< 0.1%
943.6 4
 
< 0.1%
458.83 4
 
< 0.1%
936.66 4
 
< 0.1%
762.93 4
 
< 0.1%
993.93 4
 
< 0.1%
287.72 4
 
< 0.1%
523.48 4
 
< 0.1%
Other values (25897) 29959
99.9%
ValueCountFrequency (%)
10 6
 
< 0.1%
10.01 8
< 0.1%
10.02 15
< 0.1%
10.03 5
 
< 0.1%
10.04 15
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.06 1
< 0.1%
10.12 1
< 0.1%
10.13 1
< 0.1%
10.26 1
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.06 1
< 0.1%
10.12 1
< 0.1%
10.13 1
< 0.1%
10.26 1
< 0.1%
ValueCountFrequency (%)
10 6
 
< 0.1%
10.01 8
< 0.1%
10.02 15
0.1%
10.03 5
 
< 0.1%
10.04 15
0.1%

min_single_purchase_value
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct991991
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.043848965.049664333
 Full DatasetSimple Random Sample
Minimum0.10.1
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:16.722284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum0.10.1
5-th percentile0.590.58
Q12.572.55
median5.045.07
Q37.517.52
95-th percentile9.59.51
Maximum1010
Range9.99.9
Interquartile range (IQR)4.944.97

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.8559046442.870376384
Coefficient of variation (CV)0.5662153380.5684291459
Kurtosis-1.198193882-1.208394943
Mean5.043848965.049664333
Median Absolute Deviation (MAD)2.472.49
Skewness0.002415403507-0.003530762531
Sum5043848.96151489.93
Variance8.1561913358.239060586
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:16.927005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.66 1123
 
0.1%
0.29 1112
 
0.1%
3.05 1110
 
0.1%
1.67 1101
 
0.1%
4.67 1092
 
0.1%
6.93 1092
 
0.1%
6.14 1091
 
0.1%
5.19 1091
 
0.1%
5.31 1086
 
0.1%
5.02 1086
 
0.1%
Other values (981) 989016
98.9%
ValueCountFrequency (%)
3.98 48
 
0.2%
1.77 47
 
0.2%
7.24 46
 
0.2%
6.7 45
 
0.1%
2.72 44
 
0.1%
4.99 44
 
0.1%
2.17 44
 
0.1%
2.87 44
 
0.1%
4.92 44
 
0.1%
3.75 44
 
0.1%
Other values (981) 29550
98.5%
ValueCountFrequency (%)
0.1 491
< 0.1%
0.11 1041
0.1%
0.12 1011
0.1%
0.13 1044
0.1%
0.14 1013
0.1%
ValueCountFrequency (%)
0.1 13
 
< 0.1%
0.11 28
0.1%
0.12 39
0.1%
0.13 28
0.1%
0.14 35
0.1%
ValueCountFrequency (%)
0.1 13
 
< 0.1%
0.11 28
< 0.1%
0.12 39
< 0.1%
0.13 28
< 0.1%
0.14 35
< 0.1%
ValueCountFrequency (%)
0.1 491
1.6%
0.11 1041
3.5%
0.12 1011
3.4%
0.13 1044
3.5%
0.14 1013
3.4%

product_name
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:17.169904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length99
Median length99
Mean length99
Min length99

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters9000000270000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowProduct DProduct C
2nd rowProduct CProduct A
3rd rowProduct BProduct C
4th rowProduct AProduct C
5th rowProduct CProduct B
ValueCountFrequency (%)
product 1000000
50.0%
b 250375
 
12.5%
c 249957
 
12.5%
a 249928
 
12.5%
d 249740
 
12.5%
ValueCountFrequency (%)
product 30000
50.0%
b 7644
 
12.7%
a 7534
 
12.6%
c 7443
 
12.4%
d 7379
 
12.3%
2025-06-06T01:55:17.458312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
B 7644
 
2.8%
A 7534
 
2.8%
Other values (2) 14822
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
B 7644
 
2.8%
A 7534
 
2.8%
Other values (2) 14822
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
B 7644
 
2.8%
A 7534
 
2.8%
Other values (2) 14822
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
B 7644
 
2.8%
A 7534
 
2.8%
Other values (2) 14822
5.5%

product_brand
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:17.608057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters7000000210000
Distinct characters99
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowBrand YBrand Y
2nd rowBrand XBrand Y
3rd rowBrand XBrand Z
4th rowBrand ZBrand Y
5th rowBrand XBrand X
ValueCountFrequency (%)
brand 1000000
50.0%
y 333775
 
16.7%
z 333608
 
16.7%
x 332617
 
16.6%
ValueCountFrequency (%)
brand 30000
50.0%
y 10024
 
16.7%
z 10017
 
16.7%
x 9959
 
16.6%
2025-06-06T01:55:17.870916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10024
 
4.8%
Z 10017
 
4.8%
X 9959
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10024
 
4.8%
Z 10017
 
4.8%
X 9959
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10024
 
4.8%
Z 10017
 
4.8%
X 9959
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10024
 
4.8%
Z 10017
 
4.8%
X 9959
 
4.7%

product_rating
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct4141
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.99900962.998196667
 Full DatasetSimple Random Sample
Minimum11
Maximum55
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:18.056169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile1.21.2
Q122
median33
Q344
95-th percentile4.84.8
Maximum55
Range44
Interquartile range (IQR)22

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation1.1548006031.153737456
Coefficient of variation (CV)0.38506065570.384810466
Kurtosis-1.196293362-1.192538987
Mean2.99900962.998196667
Median Absolute Deviation (MAD)11
Skewness-0.0005343871929-0.0003119056959
Sum2999009.689945.9
Variance1.3335644331.331110118
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:18.259516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2.9 25242
 
2.5%
3.4 25229
 
2.5%
2.6 25229
 
2.5%
1.3 25194
 
2.5%
3 25181
 
2.5%
4.7 25166
 
2.5%
4.3 25159
 
2.5%
4.1 25146
 
2.5%
1.6 25141
 
2.5%
4 25134
 
2.5%
Other values (31) 748179
74.8%
ValueCountFrequency (%)
4 819
 
2.7%
1.9 802
 
2.7%
3 800
 
2.7%
1.4 785
 
2.6%
3.5 779
 
2.6%
4.2 771
 
2.6%
1.2 768
 
2.6%
4.9 767
 
2.6%
1.6 767
 
2.6%
3.4 766
 
2.6%
Other values (31) 22176
73.9%
ValueCountFrequency (%)
1 12653
1.3%
1.1 24871
2.5%
1.2 25095
2.5%
1.3 25194
2.5%
1.4 24848
2.5%
ValueCountFrequency (%)
1 391
1.3%
1.1 720
2.4%
1.2 768
2.6%
1.3 735
2.5%
1.4 785
2.6%
ValueCountFrequency (%)
1 391
< 0.1%
1.1 720
0.1%
1.2 768
0.1%
1.3 735
0.1%
1.4 785
0.1%
ValueCountFrequency (%)
1 12653
42.2%
1.1 24871
82.9%
1.2 25095
83.7%
1.3 25194
84.0%
1.4 24848
82.8%

product_review_count
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct10001000
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.235198497.9591333
 Full DatasetSimple Random Sample
Minimum00
Maximum999999
Zeros98735
Zeros (%)0.1%0.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:18.475936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile5049
Q1250247
median499495
Q3749750
95-th percentile949949
Maximum999999
Range999999
Interquartile range (IQR)499503

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288.4461496289.407672
Coefficient of variation (CV)0.57777606780.5811875968
Kurtosis-1.19905271-1.209233262
Mean499.235198497.9591333
Median Absolute Deviation (MAD)250251
Skewness0.0011900144960.008984964338
Sum49923519814938774
Variance83201.1812283756.80062
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:18.689611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
974 1095
 
0.1%
56 1089
 
0.1%
769 1089
 
0.1%
725 1088
 
0.1%
683 1085
 
0.1%
229 1082
 
0.1%
501 1079
 
0.1%
937 1074
 
0.1%
384 1073
 
0.1%
497 1072
 
0.1%
Other values (990) 989174
98.9%
ValueCountFrequency (%)
226 48
 
0.2%
376 47
 
0.2%
600 47
 
0.2%
931 46
 
0.2%
357 45
 
0.1%
579 45
 
0.1%
874 45
 
0.1%
539 45
 
0.1%
868 44
 
0.1%
247 44
 
0.1%
Other values (990) 29544
98.5%
ValueCountFrequency (%)
0 987
0.1%
1 999
0.1%
2 1006
0.1%
3 1006
0.1%
4 1027
0.1%
ValueCountFrequency (%)
0 35
0.1%
1 25
0.1%
2 30
0.1%
3 26
0.1%
4 37
0.1%
ValueCountFrequency (%)
0 35
< 0.1%
1 25
< 0.1%
2 30
< 0.1%
3 26
< 0.1%
4 37
< 0.1%
ValueCountFrequency (%)
0 987
3.3%
1 999
3.3%
2 1006
3.4%
3 1006
3.4%
4 1027
3.4%

product_stock
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.51512949.48416667
 Full DatasetSimple Random Sample
Minimum00
Maximum9999
Zeros10174350
Zeros (%)1.0%1.2%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:18.903892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile54
Q12524
median4949
Q37575
95-th percentile9595
Maximum9999
Range9999
Interquartile range (IQR)5051

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.8766452928.96699706
Coefficient of variation (CV)0.58318832790.5853791023
Kurtosis-1.200520476-1.206835524
Mean49.51512949.48416667
Median Absolute Deviation (MAD)2525
Skewness0.00063837369410.004673870984
Sum495151291484525
Variance833.860643839.0869189
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:19.122748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 10261
 
1.0%
70 10245
 
1.0%
60 10187
 
1.0%
23 10175
 
1.0%
0 10174
 
1.0%
54 10171
 
1.0%
44 10148
 
1.0%
96 10147
 
1.0%
32 10138
 
1.0%
77 10136
 
1.0%
Other values (90) 898218
89.8%
ValueCountFrequency (%)
0 350
 
1.2%
96 339
 
1.1%
33 334
 
1.1%
23 331
 
1.1%
89 331
 
1.1%
35 331
 
1.1%
39 329
 
1.1%
92 328
 
1.1%
12 328
 
1.1%
70 326
 
1.1%
Other values (90) 26673
88.9%
ValueCountFrequency (%)
0 10174
1.0%
1 9857
1.0%
2 9895
1.0%
3 10030
1.0%
4 9924
1.0%
ValueCountFrequency (%)
0 350
1.2%
1 274
0.9%
2 289
1.0%
3 290
1.0%
4 317
1.1%
ValueCountFrequency (%)
0 350
< 0.1%
1 274
< 0.1%
2 289
< 0.1%
3 290
< 0.1%
4 317
< 0.1%
ValueCountFrequency (%)
0 10174
33.9%
1 9857
32.9%
2 9895
33.0%
3 10030
33.4%
4 9924
33.1%

product_return_rate
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.250137410.249805
 Full DatasetSimple Random Sample
Minimum00
Maximum0.50.5
Zeros9960280
Zeros (%)1.0%0.9%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:19.335931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile0.030.02
Q10.130.12
median0.250.25
Q30.380.38
95-th percentile0.480.48
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.250.26

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation0.14440848960.1448241616
Coefficient of variation (CV)0.57731664210.5797488504
Kurtosis-1.197824771-1.203901028
Mean0.250137410.249805
Median Absolute Deviation (MAD)0.130.13
Skewness-0.00051655697620.00145932002
Sum250137.417494.15
Variance0.020853811870.02097403778
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:19.542591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.43 20287
 
2.0%
0.38 20282
 
2.0%
0.03 20242
 
2.0%
0.46 20215
 
2.0%
0.4 20209
 
2.0%
0.14 20164
 
2.0%
0.45 20148
 
2.0%
0.16 20140
 
2.0%
0.06 20135
 
2.0%
0.29 20118
 
2.0%
Other values (41) 798060
79.8%
ValueCountFrequency (%)
0.4 651
 
2.2%
0.42 646
 
2.2%
0.16 641
 
2.1%
0.05 632
 
2.1%
0.17 631
 
2.1%
0.06 628
 
2.1%
0.46 626
 
2.1%
0.26 624
 
2.1%
0.38 624
 
2.1%
0.19 623
 
2.1%
Other values (41) 23674
78.9%
ValueCountFrequency (%)
0 9960
1.0%
0.01 19921
2.0%
0.02 19994
2.0%
0.03 20242
2.0%
0.04 19825
2.0%
ValueCountFrequency (%)
0 280
0.9%
0.01 619
2.1%
0.02 619
2.1%
0.03 603
2.0%
0.04 616
2.1%
ValueCountFrequency (%)
0 280
< 0.1%
0.01 619
0.1%
0.02 619
0.1%
0.03 603
0.1%
0.04 616
0.1%
ValueCountFrequency (%)
0 9960
33.2%
0.01 19921
66.4%
0.02 19994
66.6%
0.03 20242
67.5%
0.04 19825
66.1%

product_size
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:19.767258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length55
Mean length5.3335015.3356
Min length55

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters5333501160068
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowSmallSmall
2nd rowMediumMedium
3rd rowMediumLarge
4th rowLargeSmall
5th rowSmallLarge
ValueCountFrequency (%)
large 333964
33.4%
medium 333501
33.4%
small 332535
33.3%
ValueCountFrequency (%)
small 10108
33.7%
medium 10068
33.6%
large 9824
32.7%
2025-06-06T01:55:20.061818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
l 20216
12.6%
m 20176
12.6%
a 19932
12.5%
e 19892
12.4%
S 10108
6.3%
M 10068
6.3%
d 10068
6.3%
i 10068
6.3%
u 10068
6.3%
L 9824
6.1%
Other values (2) 19648
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 160068
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
l 20216
12.6%
m 20176
12.6%
a 19932
12.5%
e 19892
12.4%
S 10108
6.3%
M 10068
6.3%
d 10068
6.3%
i 10068
6.3%
u 10068
6.3%
L 9824
6.1%
Other values (2) 19648
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 160068
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
l 20216
12.6%
m 20176
12.6%
a 19932
12.5%
e 19892
12.4%
S 10108
6.3%
M 10068
6.3%
d 10068
6.3%
i 10068
6.3%
u 10068
6.3%
L 9824
6.1%
Other values (2) 19648
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 160068
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
l 20216
12.6%
m 20176
12.6%
a 19932
12.5%
e 19892
12.4%
S 10108
6.3%
M 10068
6.3%
d 10068
6.3%
i 10068
6.3%
u 10068
6.3%
L 9824
6.1%
Other values (2) 19648
12.3%

product_weight
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct991991
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.054372385.044035667
 Full DatasetSimple Random Sample
Minimum0.10.1
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:20.262637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum0.10.1
5-th percentile0.60.6
Q12.582.57
median5.065.04
Q37.537.51
95-th percentile9.59.48
Maximum1010
Range9.99.9
Interquartile range (IQR)4.954.94

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation2.8578484872.849706562
Coefficient of variation (CV)0.565421040.5649655852
Kurtosis-1.200012392-1.193909764
Mean5.054372385.044035667
Median Absolute Deviation (MAD)2.472.47
Skewness-0.001975515497-0.0005143389772
Sum5054372.38151321.07
Variance8.1672979778.120827491
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:20.480808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.51 1094
 
0.1%
7.79 1092
 
0.1%
3.96 1089
 
0.1%
3.55 1089
 
0.1%
1.61 1088
 
0.1%
5.24 1088
 
0.1%
1.74 1087
 
0.1%
4.66 1085
 
0.1%
3.04 1082
 
0.1%
1.22 1081
 
0.1%
Other values (981) 989125
98.9%
ValueCountFrequency (%)
1.61 50
 
0.2%
1.41 48
 
0.2%
0.94 46
 
0.2%
4.36 45
 
0.1%
7.79 44
 
0.1%
5.85 44
 
0.1%
7.84 44
 
0.1%
7.15 44
 
0.1%
5.47 44
 
0.1%
2.3 44
 
0.1%
Other values (981) 29547
98.5%
ValueCountFrequency (%)
0.1 506
0.1%
0.11 1031
0.1%
0.12 996
0.1%
0.13 1001
0.1%
0.14 1007
0.1%
ValueCountFrequency (%)
0.1 18
0.1%
0.11 36
0.1%
0.12 33
0.1%
0.13 31
0.1%
0.14 30
0.1%
ValueCountFrequency (%)
0.1 18
< 0.1%
0.11 36
< 0.1%
0.12 33
< 0.1%
0.13 31
< 0.1%
0.14 30
< 0.1%
ValueCountFrequency (%)
0.1 506
1.7%
0.11 1031
3.4%
0.12 996
3.3%
0.13 1001
3.3%
0.14 1007
3.4%

product_color
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:20.765517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length55
Median length55
Mean length4.3993974.394533333
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters4399397131836
Distinct characters1616
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowRedGreen
2nd rowBlueRed
3rd rowGreenGreen
4th rowBlueBlack
5th rowRedRed
ValueCountFrequency (%)
blue 200671
20.1%
green 200202
20.0%
red 199966
20.0%
black 199704
20.0%
white 199457
19.9%
ValueCountFrequency (%)
red 6078
20.3%
black 6077
20.3%
white 6034
20.1%
blue 6008
20.0%
green 5803
19.3%
2025-06-06T01:55:21.644595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 29726
22.5%
B 12085
 
9.2%
l 12085
 
9.2%
R 6078
 
4.6%
d 6078
 
4.6%
a 6077
 
4.6%
c 6077
 
4.6%
k 6077
 
4.6%
W 6034
 
4.6%
h 6034
 
4.6%
Other values (6) 35485
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 131836
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 29726
22.5%
B 12085
 
9.2%
l 12085
 
9.2%
R 6078
 
4.6%
d 6078
 
4.6%
a 6077
 
4.6%
c 6077
 
4.6%
k 6077
 
4.6%
W 6034
 
4.6%
h 6034
 
4.6%
Other values (6) 35485
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 131836
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 29726
22.5%
B 12085
 
9.2%
l 12085
 
9.2%
R 6078
 
4.6%
d 6078
 
4.6%
a 6077
 
4.6%
c 6077
 
4.6%
k 6077
 
4.6%
W 6034
 
4.6%
h 6034
 
4.6%
Other values (6) 35485
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 131836
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 29726
22.5%
B 12085
 
9.2%
l 12085
 
9.2%
R 6078
 
4.6%
d 6078
 
4.6%
a 6077
 
4.6%
c 6077
 
4.6%
k 6077
 
4.6%
W 6034
 
4.6%
h 6034
 
4.6%
Other values (6) 35485
26.9%

product_material
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:21.859818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length77
Median length55
Mean length5.250875.2382
Min length44

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters5250870157146
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowMetalMetal
2nd rowMetalMetal
3rd rowPlasticWood
4th rowWoodWood
5th rowMetalWood
ValueCountFrequency (%)
plastic 250483
25.0%
wood 250096
25.0%
metal 249896
25.0%
glass 249525
25.0%
ValueCountFrequency (%)
metal 7578
25.3%
glass 7551
25.2%
wood 7532
25.1%
plastic 7339
24.5%
2025-06-06T01:55:22.193325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
l 22468
14.3%
a 22468
14.3%
s 22441
14.3%
o 15064
9.6%
t 14917
9.5%
e 7578
 
4.8%
M 7578
 
4.8%
G 7551
 
4.8%
W 7532
 
4.8%
d 7532
 
4.8%
Other values (3) 22017
14.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157146
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
l 22468
14.3%
a 22468
14.3%
s 22441
14.3%
o 15064
9.6%
t 14917
9.5%
e 7578
 
4.8%
M 7578
 
4.8%
G 7551
 
4.8%
W 7532
 
4.8%
d 7532
 
4.8%
Other values (3) 22017
14.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157146
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
l 22468
14.3%
a 22468
14.3%
s 22441
14.3%
o 15064
9.6%
t 14917
9.5%
e 7578
 
4.8%
M 7578
 
4.8%
G 7551
 
4.8%
W 7532
 
4.8%
d 7532
 
4.8%
Other values (3) 22017
14.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157146
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
l 22468
14.3%
a 22468
14.3%
s 22441
14.3%
o 15064
9.6%
t 14917
9.5%
e 7578
 
4.8%
M 7578
 
4.8%
G 7551
 
4.8%
W 7532
 
4.8%
d 7532
 
4.8%
Other values (3) 22017
14.0%

product_manufacture_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct99203729994
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:22.858152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique98412629988 ?
Unique (%)98.4%> 99.9%

Sample

 Full DatasetSimple Random Sample
1st row2019-08-04 01:47:012018-01-06 20:55:23
2nd row2019-10-23 19:59:172019-08-27 15:56:58
3rd row2018-05-12 08:00:292019-10-18 02:37:55
4th row2019-11-15 16:17:292019-06-25 11:14:35
5th row2019-08-27 02:58:192018-02-07 11:19:34
ValueCountFrequency (%)
2018-04-10 1514
 
0.1%
2019-03-19 1490
 
0.1%
2018-02-26 1471
 
0.1%
2018-06-18 1467
 
0.1%
2018-09-24 1462
 
0.1%
2019-01-25 1457
 
0.1%
2019-01-30 1456
 
0.1%
2018-04-28 1454
 
0.1%
2019-07-04 1453
 
0.1%
2019-01-09 1453
 
0.1%
Other values (87119) 1985323
99.3%
ValueCountFrequency (%)
2019-02-15 61
 
0.1%
2019-09-06 59
 
0.1%
2019-09-11 59
 
0.1%
2018-11-27 59
 
0.1%
2018-02-22 59
 
0.1%
2019-10-15 59
 
0.1%
2019-03-13 59
 
0.1%
2018-02-26 57
 
0.1%
2019-03-19 57
 
0.1%
2018-02-12 57
 
0.1%
Other values (26006) 59414
99.0%
2025-06-06T01:55:23.990214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98883
17.3%
1 88211
15.5%
2 72490
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
8 28892
 
5.1%
9 28884
 
5.1%
3 26866
 
4.7%
4 24017
 
4.2%
Other values (3) 51757
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98883
17.3%
1 88211
15.5%
2 72490
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
8 28892
 
5.1%
9 28884
 
5.1%
3 26866
 
4.7%
4 24017
 
4.2%
Other values (3) 51757
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98883
17.3%
1 88211
15.5%
2 72490
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
8 28892
 
5.1%
9 28884
 
5.1%
3 26866
 
4.7%
4 24017
 
4.2%
Other values (3) 51757
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98883
17.3%
1 88211
15.5%
2 72490
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
8 28892
 
5.1%
9 28884
 
5.1%
3 26866
 
4.7%
4 24017
 
4.2%
Other values (3) 51757
9.1%

product_expiry_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct99204229994
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:24.961549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique98412129988 ?
Unique (%)98.4%> 99.9%

Sample

 Full DatasetSimple Random Sample
1st row2022-05-28 14:54:022023-08-23 12:03:16
2nd row2022-12-19 08:04:412022-01-11 23:20:05
3rd row2023-02-01 12:15:072023-06-27 20:04:25
4th row2023-02-05 11:46:572022-11-09 01:40:41
5th row2023-10-05 08:13:072023-12-24 16:31:14
ValueCountFrequency (%)
2022-12-22 1476
 
0.1%
2022-06-08 1475
 
0.1%
2022-01-28 1473
 
0.1%
2023-03-13 1472
 
0.1%
2022-10-06 1468
 
0.1%
2022-06-27 1468
 
0.1%
2023-07-08 1457
 
0.1%
2023-07-23 1457
 
0.1%
2023-01-11 1452
 
0.1%
2022-04-17 1450
 
0.1%
Other values (87119) 1985352
99.3%
ValueCountFrequency (%)
2023-07-15 63
 
0.1%
2023-09-03 61
 
0.1%
2022-03-27 60
 
0.1%
2023-01-25 58
 
0.1%
2023-07-11 58
 
0.1%
2022-05-09 57
 
0.1%
2023-03-16 57
 
0.1%
2023-04-05 57
 
0.1%
2023-07-04 57
 
0.1%
2022-07-31 57
 
0.1%
Other values (26132) 59415
99.0%
2025-06-06T01:55:26.121585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117355
20.6%
0 98915
17.4%
- 60000
10.5%
: 60000
10.5%
1 57871
10.2%
3 41938
 
7.4%
30000
 
5.3%
5 24166
 
4.2%
4 24028
 
4.2%
7 14001
 
2.5%
Other values (3) 41726
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117355
20.6%
0 98915
17.4%
- 60000
10.5%
: 60000
10.5%
1 57871
10.2%
3 41938
 
7.4%
30000
 
5.3%
5 24166
 
4.2%
4 24028
 
4.2%
7 14001
 
2.5%
Other values (3) 41726
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117355
20.6%
0 98915
17.4%
- 60000
10.5%
: 60000
10.5%
1 57871
10.2%
3 41938
 
7.4%
30000
 
5.3%
5 24166
 
4.2%
4 24028
 
4.2%
7 14001
 
2.5%
Other values (3) 41726
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117355
20.6%
0 98915
17.4%
- 60000
10.5%
: 60000
10.5%
1 57871
10.2%
3 41938
 
7.4%
30000
 
5.3%
5 24166
 
4.2%
4 24028
 
4.2%
7 14001
 
2.5%
Other values (3) 41726
 
7.3%

product_shelf_life
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct365365
Distinct (%)< 0.1%1.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean181.876207181.7763333
 Full DatasetSimple Random Sample
Minimum00
Maximum364364
Zeros271387
Zeros (%)0.3%0.3%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:26.298014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile1818
Q19190
median182183
Q3273273
95-th percentile346346
Maximum364364
Range364364
Interquartile range (IQR)182183

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation105.2288552105.2746763
Coefficient of variation (CV)0.57857405850.5791440192
Kurtosis-1.198082782-1.199467241
Mean181.876207181.7763333
Median Absolute Deviation (MAD)9191
Skewness0.0006229204449-0.002884577034
Sum1818762075453290
Variance11073.1119711082.75747
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:26.506192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
87 2893
 
0.3%
272 2874
 
0.3%
70 2870
 
0.3%
250 2870
 
0.3%
210 2862
 
0.3%
224 2859
 
0.3%
238 2857
 
0.3%
33 2848
 
0.3%
297 2847
 
0.3%
171 2845
 
0.3%
Other values (355) 971375
97.1%
ValueCountFrequency (%)
59 110
 
0.4%
307 109
 
0.4%
291 108
 
0.4%
20 106
 
0.4%
121 104
 
0.3%
253 104
 
0.3%
177 103
 
0.3%
269 102
 
0.3%
67 101
 
0.3%
237 101
 
0.3%
Other values (355) 28952
96.5%
ValueCountFrequency (%)
0 2713
0.3%
1 2788
0.3%
2 2776
0.3%
3 2725
0.3%
4 2788
0.3%
ValueCountFrequency (%)
0 87
0.3%
1 84
0.3%
2 89
0.3%
3 81
0.3%
4 68
0.2%
ValueCountFrequency (%)
0 87
< 0.1%
1 84
< 0.1%
2 89
< 0.1%
3 81
< 0.1%
4 68
< 0.1%
ValueCountFrequency (%)
0 2713
9.0%
1 2788
9.3%
2 2776
9.3%
3 2725
9.1%
4 2788
9.3%

promotion_id
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct999999
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.920037504.7921333
 Full DatasetSimple Random Sample
Minimum11
Maximum999999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:26.739413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum11
5-th percentile5051
Q1250259
median500505
Q3750754
95-th percentile949952
Maximum999999
Range998998
Interquartile range (IQR)500495

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation288.4530565287.9883386
Coefficient of variation (CV)0.576998390.570508769
Kurtosis-1.200677574-1.188711465
Mean499.920037504.7921333
Median Absolute Deviation (MAD)250248
Skewness-0.0008935044332-0.0185586277
Sum49992003715143764
Variance83205.1657982937.28317
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:26.936810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52 1092
 
0.1%
94 1082
 
0.1%
374 1079
 
0.1%
117 1077
 
0.1%
29 1075
 
0.1%
603 1075
 
0.1%
512 1073
 
0.1%
949 1073
 
0.1%
885 1073
 
0.1%
51 1070
 
0.1%
Other values (989) 989231
98.9%
ValueCountFrequency (%)
141 53
 
0.2%
754 50
 
0.2%
857 50
 
0.2%
394 47
 
0.2%
959 46
 
0.2%
762 46
 
0.2%
333 45
 
0.1%
691 45
 
0.1%
998 45
 
0.1%
400 44
 
0.1%
Other values (989) 29529
98.4%
ValueCountFrequency (%)
1 1033
0.1%
2 995
0.1%
3 1036
0.1%
4 1024
0.1%
5 992
0.1%
ValueCountFrequency (%)
1 31
0.1%
2 32
0.1%
3 23
0.1%
4 33
0.1%
5 29
0.1%
ValueCountFrequency (%)
1 31
< 0.1%
2 32
< 0.1%
3 23
< 0.1%
4 33
< 0.1%
5 29
< 0.1%
ValueCountFrequency (%)
1 1033
3.4%
2 995
3.3%
3 1036
3.5%
4 1024
3.4%
5 992
3.3%

promotion_type
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:27.178216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length2020
Median length1010
Mean length12.33406412.32456667
Min length77

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters12334064369737
Distinct characters2020
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st row20% Off20% Off
2nd rowFlash Sale20% Off
3rd rowFlash SaleBuy One Get One Free
4th rowBuy One Get One FreeFlash Sale
5th rowFlash Sale20% Off
ValueCountFrequency (%)
one 667040
22.2%
20 333712
11.1%
off 333712
11.1%
buy 333520
11.1%
get 333520
11.1%
free 333520
11.1%
flash 332768
11.1%
sale 332768
11.1%
ValueCountFrequency (%)
one 19954
22.2%
flash 10012
11.1%
sale 10012
11.1%
20 10011
11.1%
off 10011
11.1%
buy 9977
11.1%
get 9977
11.1%
free 9977
11.1%
2025-06-06T01:55:27.501065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
59931
16.2%
e 59897
16.2%
O 29965
 
8.1%
l 20024
 
5.4%
a 20024
 
5.4%
f 20022
 
5.4%
F 19989
 
5.4%
n 19954
 
5.4%
s 10012
 
2.7%
h 10012
 
2.7%
Other values (10) 99907
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 369737
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
59931
16.2%
e 59897
16.2%
O 29965
 
8.1%
l 20024
 
5.4%
a 20024
 
5.4%
f 20022
 
5.4%
F 19989
 
5.4%
n 19954
 
5.4%
s 10012
 
2.7%
h 10012
 
2.7%
Other values (10) 99907
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 369737
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
59931
16.2%
e 59897
16.2%
O 29965
 
8.1%
l 20024
 
5.4%
a 20024
 
5.4%
f 20022
 
5.4%
F 19989
 
5.4%
n 19954
 
5.4%
s 10012
 
2.7%
h 10012
 
2.7%
Other values (10) 99907
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 369737
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
59931
16.2%
e 59897
16.2%
O 29965
 
8.1%
l 20024
 
5.4%
a 20024
 
5.4%
f 20022
 
5.4%
F 19989
 
5.4%
n 19954
 
5.4%
s 10012
 
2.7%
h 10012
 
2.7%
Other values (10) 99907
27.0%

promotion_start_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct98425829982
Distinct (%)98.4%99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:28.188806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique96868129964 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSimple Random Sample
1st row2021-07-14 14:28:422021-02-17 01:32:19
2nd row2021-09-23 04:26:092021-12-04 10:56:59
3rd row2021-06-13 12:31:152021-10-28 00:30:15
4th row2021-05-23 05:42:482021-01-07 01:30:47
5th row2021-04-19 04:55:322021-02-20 20:32:57
ValueCountFrequency (%)
2021-03-05 2885
 
0.1%
2021-02-07 2874
 
0.1%
2021-06-23 2871
 
0.1%
2021-05-15 2867
 
0.1%
2021-08-27 2863
 
0.1%
2021-11-04 2862
 
0.1%
2021-03-25 2858
 
0.1%
2021-09-06 2854
 
0.1%
2021-12-21 2851
 
0.1%
2021-08-06 2850
 
0.1%
Other values (86754) 1971365
98.6%
ValueCountFrequency (%)
2021-04-14 111
 
0.2%
2021-01-20 111
 
0.2%
2021-12-05 111
 
0.2%
2021-05-26 108
 
0.2%
2021-09-14 106
 
0.2%
2021-06-05 106
 
0.2%
2021-09-10 104
 
0.2%
2021-05-03 102
 
0.2%
2021-06-08 101
 
0.2%
2021-11-29 100
 
0.2%
Other values (25741) 58940
98.2%
2025-06-06T01:55:28.988124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102386
18.0%
0 98882
17.3%
1 88284
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26705
 
4.7%
5 24123
 
4.2%
4 23870
 
4.2%
6 13992
 
2.5%
Other values (3) 41758
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102386
18.0%
0 98882
17.3%
1 88284
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26705
 
4.7%
5 24123
 
4.2%
4 23870
 
4.2%
6 13992
 
2.5%
Other values (3) 41758
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102386
18.0%
0 98882
17.3%
1 88284
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26705
 
4.7%
5 24123
 
4.2%
4 23870
 
4.2%
6 13992
 
2.5%
Other values (3) 41758
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102386
18.0%
0 98882
17.3%
1 88284
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26705
 
4.7%
5 24123
 
4.2%
4 23870
 
4.2%
6 13992
 
2.5%
Other values (3) 41758
7.3%

promotion_end_date
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct98425229988
Distinct (%)98.4%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:29.667646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique96867629976 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSimple Random Sample
1st row2022-12-30 13:04:132022-09-29 05:44:20
2nd row2022-09-13 03:16:262022-10-12 00:25:34
3rd row2022-03-13 00:53:352022-11-05 14:46:21
4th row2022-02-06 00:42:302022-08-12 01:18:49
5th row2022-12-04 13:07:092022-09-08 12:55:31
ValueCountFrequency (%)
2022-08-06 2905
 
0.1%
2022-03-08 2896
 
0.1%
2022-09-28 2874
 
0.1%
2022-02-22 2873
 
0.1%
2022-09-16 2872
 
0.1%
2022-06-10 2865
 
0.1%
2022-07-13 2858
 
0.1%
2022-12-15 2854
 
0.1%
2022-12-31 2847
 
0.1%
2022-08-25 2842
 
0.1%
Other values (86755) 1971314
98.6%
ValueCountFrequency (%)
2022-12-01 114
 
0.2%
2022-09-11 113
 
0.2%
2022-07-03 113
 
0.2%
2022-02-15 111
 
0.2%
2022-10-23 109
 
0.2%
2022-09-08 105
 
0.2%
2022-04-17 103
 
0.2%
2022-07-21 102
 
0.2%
2022-11-11 102
 
0.2%
2022-06-06 102
 
0.2%
Other values (25640) 58926
98.2%
2025-06-06T01:55:30.419798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132089
23.2%
0 99325
17.4%
- 60000
10.5%
: 60000
10.5%
1 58117
10.2%
30000
 
5.3%
3 26712
 
4.7%
4 23940
 
4.2%
5 23864
 
4.2%
8 14141
 
2.5%
Other values (3) 41812
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132089
23.2%
0 99325
17.4%
- 60000
10.5%
: 60000
10.5%
1 58117
10.2%
30000
 
5.3%
3 26712
 
4.7%
4 23940
 
4.2%
5 23864
 
4.2%
8 14141
 
2.5%
Other values (3) 41812
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132089
23.2%
0 99325
17.4%
- 60000
10.5%
: 60000
10.5%
1 58117
10.2%
30000
 
5.3%
3 26712
 
4.7%
4 23940
 
4.2%
5 23864
 
4.2%
8 14141
 
2.5%
Other values (3) 41812
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132089
23.2%
0 99325
17.4%
- 60000
10.5%
: 60000
10.5%
1 58117
10.2%
30000
 
5.3%
3 26712
 
4.7%
4 23940
 
4.2%
5 23864
 
4.2%
8 14141
 
2.5%
Other values (3) 41812
 
7.3%

promotion_effectiveness
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:30.632403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length44
Mean length4.3334074.3349
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters4333407130047
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowHighMedium
2nd rowLowHigh
3rd rowLowLow
4th rowHighHigh
5th rowMediumHigh
ValueCountFrequency (%)
high 333660
33.4%
medium 333249
33.3%
low 333091
33.3%
ValueCountFrequency (%)
high 10116
33.7%
medium 9977
33.3%
low 9907
33.0%
2025-06-06T01:55:30.961828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 20093
15.5%
H 10116
7.8%
g 10116
7.8%
h 10116
7.8%
M 9977
7.7%
e 9977
7.7%
d 9977
7.7%
u 9977
7.7%
m 9977
7.7%
L 9907
7.6%
Other values (2) 19814
15.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130047
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 20093
15.5%
H 10116
7.8%
g 10116
7.8%
h 10116
7.8%
M 9977
7.7%
e 9977
7.7%
d 9977
7.7%
u 9977
7.7%
m 9977
7.7%
L 9907
7.6%
Other values (2) 19814
15.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130047
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 20093
15.5%
H 10116
7.8%
g 10116
7.8%
h 10116
7.8%
M 9977
7.7%
e 9977
7.7%
d 9977
7.7%
u 9977
7.7%
m 9977
7.7%
L 9907
7.6%
Other values (2) 19814
15.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130047
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 20093
15.5%
H 10116
7.8%
g 10116
7.8%
h 10116
7.8%
M 9977
7.7%
e 9977
7.7%
d 9977
7.7%
u 9977
7.7%
m 9977
7.7%
L 9907
7.6%
Other values (2) 19814
15.2%

promotion_channel
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:31.165577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1212
Median length88
Mean length8.6654288.661933333
Min length66

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters8665428259858
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowOnlineIn-store
2nd rowSocial MediaOnline
3rd rowOnlineSocial Media
4th rowSocial MediaIn-store
5th rowOnlineOnline
ValueCountFrequency (%)
online 333694
25.0%
social 333204
25.0%
media 333204
25.0%
in-store 333102
25.0%
ValueCountFrequency (%)
in-store 10076
25.2%
online 9973
25.0%
social 9951
24.9%
media 9951
24.9%
2025-06-06T01:55:31.509108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30022
11.6%
e 30000
11.5%
i 29875
11.5%
o 20027
 
7.7%
l 19924
 
7.7%
a 19902
 
7.7%
I 10076
 
3.9%
t 10076
 
3.9%
- 10076
 
3.9%
s 10076
 
3.9%
Other values (7) 69804
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259858
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30022
11.6%
e 30000
11.5%
i 29875
11.5%
o 20027
 
7.7%
l 19924
 
7.7%
a 19902
 
7.7%
I 10076
 
3.9%
t 10076
 
3.9%
- 10076
 
3.9%
s 10076
 
3.9%
Other values (7) 69804
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259858
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30022
11.6%
e 30000
11.5%
i 29875
11.5%
o 20027
 
7.7%
l 19924
 
7.7%
a 19902
 
7.7%
I 10076
 
3.9%
t 10076
 
3.9%
- 10076
 
3.9%
s 10076
 
3.9%
Other values (7) 69804
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259858
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30022
11.6%
e 30000
11.5%
i 29875
11.5%
o 20027
 
7.7%
l 19924
 
7.7%
a 19902
 
7.7%
I 10076
 
3.9%
t 10076
 
3.9%
- 10076
 
3.9%
s 10076
 
3.9%
Other values (7) 69804
26.9%
 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:31.696646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length1919
Median length1319
Mean length15.99929216.02
Min length1313

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters15999292480600
Distinct characters1515
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowNew CustomersNew Customers
2nd rowNew CustomersReturning Customers
3rd rowNew CustomersNew Customers
4th rowReturning CustomersReturning Customers
5th rowNew CustomersNew Customers
ValueCountFrequency (%)
customers 1000000
50.0%
new 500118
25.0%
returning 499882
25.0%
ValueCountFrequency (%)
customers 30000
50.0%
returning 15100
25.2%
new 14900
24.8%
2025-06-06T01:55:31.998409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45100
9.4%
r 45100
9.4%
u 45100
9.4%
n 30200
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75100
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480600
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45100
9.4%
r 45100
9.4%
u 45100
9.4%
n 30200
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75100
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480600
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45100
9.4%
r 45100
9.4%
u 45100
9.4%
n 30200
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75100
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480600
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45100
9.4%
r 45100
9.4%
u 45100
9.4%
n 30200
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75100
15.6%

customer_zip_code
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct8999925515
Distinct (%)9.0%85.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean54993.6447755071.13573
 Full DatasetSimple Random Sample
Minimum1000010000
Maximum9999899998
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:32.163410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1000010000
5-th percentile1449114634.85
Q132477.7532793
median5496655060.5
Q37749377457.25
95-th percentile9549795560.1
Maximum9999899998
Range8999889998
Interquartile range (IQR)45015.2544664.25

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation25975.807825897.25074
Coefficient of variation (CV)0.47234199340.4702508927
Kurtosis-1.199859176-1.184604656
Mean54993.6447755071.13573
Median Absolute Deviation (MAD)2250922332
Skewness0.000792464580.001977937745
Sum5.499364477 × 10101652134072
Variance674742590.8670667596.1
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:32.367526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41138 27
 
< 0.1%
28225 27
 
< 0.1%
19719 27
 
< 0.1%
25427 27
 
< 0.1%
95120 26
 
< 0.1%
38515 26
 
< 0.1%
54735 26
 
< 0.1%
21109 26
 
< 0.1%
17611 25
 
< 0.1%
82394 25
 
< 0.1%
Other values (89989) 999738
> 99.9%
ValueCountFrequency (%)
18116 5
 
< 0.1%
55723 5
 
< 0.1%
50060 5
 
< 0.1%
80607 5
 
< 0.1%
63810 4
 
< 0.1%
16152 4
 
< 0.1%
31460 4
 
< 0.1%
70590 4
 
< 0.1%
67725 4
 
< 0.1%
84885 4
 
< 0.1%
Other values (25505) 29956
99.9%
ValueCountFrequency (%)
10000 12
< 0.1%
10001 14
< 0.1%
10002 6
< 0.1%
10003 12
< 0.1%
10004 5
 
< 0.1%
ValueCountFrequency (%)
10000 1
< 0.1%
10006 1
< 0.1%
10007 1
< 0.1%
10009 1
< 0.1%
10011 1
< 0.1%
ValueCountFrequency (%)
10000 1
< 0.1%
10006 1
< 0.1%
10007 1
< 0.1%
10009 1
< 0.1%
10011 1
< 0.1%
ValueCountFrequency (%)
10000 12
< 0.1%
10001 14
< 0.1%
10002 6
< 0.1%
10003 12
< 0.1%
10004 5
 
< 0.1%

customer_city
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:32.556709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters6000000180000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowCity DCity B
2nd rowCity ACity A
3rd rowCity BCity D
4th rowCity ACity D
5th rowCity BCity C
ValueCountFrequency (%)
city 1000000
50.0%
b 250788
 
12.5%
c 249955
 
12.5%
a 249698
 
12.5%
d 249559
 
12.5%
ValueCountFrequency (%)
city 30000
50.0%
d 7579
 
12.6%
c 7503
 
12.5%
b 7480
 
12.5%
a 7438
 
12.4%
2025-06-06T01:55:32.808890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37503
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7579
 
4.2%
B 7480
 
4.2%
A 7438
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37503
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7579
 
4.2%
B 7480
 
4.2%
A 7438
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37503
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7579
 
4.2%
B 7480
 
4.2%
A 7438
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37503
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7579
 
4.2%
B 7480
 
4.2%
A 7438
 
4.1%

customer_state
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:32.958817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters7000000210000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowState YState X
2nd rowState XState Y
3rd rowState XState Y
4th rowState YState Y
5th rowState ZState Z
ValueCountFrequency (%)
state 1000000
50.0%
z 333674
 
16.7%
x 333196
 
16.7%
y 333130
 
16.7%
ValueCountFrequency (%)
state 30000
50.0%
y 10136
 
16.9%
x 10063
 
16.8%
z 9801
 
16.3%
2025-06-06T01:55:33.213864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Y 10136
 
4.8%
X 10063
 
4.8%
Z 9801
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Y 10136
 
4.8%
X 10063
 
4.8%
Z 9801
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Y 10136
 
4.8%
X 10063
 
4.8%
Z 9801
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Y 10136
 
4.8%
X 10063
 
4.8%
Z 9801
 
4.7%

store_zip_code
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct8999925490
Distinct (%)9.0%85.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean54972.7667154746.83927
 Full DatasetSimple Random Sample
Minimum1000010000
Maximum9999899998
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:33.382676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum1000010000
5-th percentile1448814340.95
Q13247332161.5
median5496154635.5
Q37745177232.75
95-th percentile9547095500.25
Maximum9999899998
Range8999889998
Interquartile range (IQR)4497845071.25

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation25981.4831426022.16761
Coefficient of variation (CV)0.47262462290.4753181728
Kurtosis-1.200166165-1.19622933
Mean54972.7667154746.83927
Median Absolute Deviation (MAD)22489.522554
Skewness-0.00010396262030.01267849452
Sum5.497276671 × 10101642405178
Variance675037466.1677153207.1
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:33.589806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20956 28
 
< 0.1%
29159 27
 
< 0.1%
59836 26
 
< 0.1%
54696 26
 
< 0.1%
92910 26
 
< 0.1%
43369 26
 
< 0.1%
26386 26
 
< 0.1%
90024 26
 
< 0.1%
27134 26
 
< 0.1%
20477 26
 
< 0.1%
Other values (89989) 999737
> 99.9%
ValueCountFrequency (%)
73917 4
 
< 0.1%
34041 4
 
< 0.1%
52908 4
 
< 0.1%
43913 4
 
< 0.1%
55324 4
 
< 0.1%
94397 4
 
< 0.1%
18531 4
 
< 0.1%
14972 4
 
< 0.1%
15442 4
 
< 0.1%
63051 4
 
< 0.1%
Other values (25480) 29960
99.9%
ValueCountFrequency (%)
10000 11
< 0.1%
10001 6
 
< 0.1%
10002 15
< 0.1%
10003 8
< 0.1%
10004 14
< 0.1%
ValueCountFrequency (%)
10000 1
< 0.1%
10001 1
< 0.1%
10007 1
< 0.1%
10011 1
< 0.1%
10012 1
< 0.1%
ValueCountFrequency (%)
10000 1
< 0.1%
10001 1
< 0.1%
10007 1
< 0.1%
10011 1
< 0.1%
10012 1
< 0.1%
ValueCountFrequency (%)
10000 11
< 0.1%
10001 6
 
< 0.1%
10002 15
0.1%
10003 8
< 0.1%
10004 14
< 0.1%

store_city
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:33.774030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters6000000180000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowCity DCity C
2nd rowCity CCity A
3rd rowCity ACity A
4th rowCity BCity C
5th rowCity CCity A
ValueCountFrequency (%)
city 1000000
50.0%
d 250315
 
12.5%
c 250177
 
12.5%
b 249965
 
12.5%
a 249543
 
12.5%
ValueCountFrequency (%)
city 30000
50.0%
c 7582
 
12.6%
d 7533
 
12.6%
b 7469
 
12.4%
a 7416
 
12.4%
2025-06-06T01:55:34.023611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37582
20.9%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7533
 
4.2%
B 7469
 
4.1%
A 7416
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37582
20.9%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7533
 
4.2%
B 7469
 
4.1%
A 7416
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37582
20.9%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7533
 
4.2%
B 7469
 
4.1%
A 7416
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37582
20.9%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7533
 
4.2%
B 7469
 
4.1%
A 7416
 
4.1%

store_state
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:34.169387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters7000000210000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowState YState Z
2nd rowState XState Y
3rd rowState YState X
4th rowState ZState Y
5th rowState XState Z
ValueCountFrequency (%)
state 1000000
50.0%
x 333702
 
16.7%
z 333602
 
16.7%
y 332696
 
16.6%
ValueCountFrequency (%)
state 30000
50.0%
x 10033
 
16.7%
z 10016
 
16.7%
y 9951
 
16.6%
2025-06-06T01:55:34.452446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10033
 
4.8%
Z 10016
 
4.8%
Y 9951
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10033
 
4.8%
Z 10016
 
4.8%
Y 9951
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10033
 
4.8%
Z 10016
 
4.8%
Y 9951
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10033
 
4.8%
Z 10016
 
4.8%
Y 9951
 
4.7%

distance_to_store
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100019504
Distinct (%)1.0%31.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.9791092450.04898367
 Full DatasetSimple Random Sample
Minimum00
Maximum100100
Zeros622
Zeros (%)< 0.1%< 0.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:34.608762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile5.034.93
Q124.9725.1275
median49.9650.01
Q374.9575.02
95-th percentile94.9894.99
Maximum100100
Range100100
Interquartile range (IQR)49.9849.8925

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.8609891128.89155462
Coefficient of variation (CV)0.57746105430.5772655608
Kurtosis-1.200199633-1.203311878
Mean49.9791092450.04898367
Median Absolute Deviation (MAD)24.9924.94
Skewness0.001218286468-0.001316464469
Sum49979109.241501469.51
Variance832.9566927834.7219286
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:34.808326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.05 139
 
< 0.1%
0.01 138
 
< 0.1%
9.68 138
 
< 0.1%
30.79 136
 
< 0.1%
31.27 135
 
< 0.1%
22.61 134
 
< 0.1%
40.84 134
 
< 0.1%
78.41 134
 
< 0.1%
82.37 133
 
< 0.1%
89.9 133
 
< 0.1%
Other values (9991) 998646
99.9%
ValueCountFrequency (%)
30.13 14
 
< 0.1%
29.63 11
 
< 0.1%
4.33 11
 
< 0.1%
87.31 11
 
< 0.1%
44.66 10
 
< 0.1%
94.47 10
 
< 0.1%
71.65 10
 
< 0.1%
88.95 10
 
< 0.1%
92.22 10
 
< 0.1%
94.42 10
 
< 0.1%
Other values (9494) 29893
99.6%
ValueCountFrequency (%)
0 62
< 0.1%
0.01 138
< 0.1%
0.02 88
< 0.1%
0.03 113
< 0.1%
0.04 86
< 0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
0.01 4
< 0.1%
0.02 2
 
< 0.1%
0.03 6
< 0.1%
0.04 2
 
< 0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
0.01 4
< 0.1%
0.02 2
 
< 0.1%
0.03 6
< 0.1%
0.04 2
 
< 0.1%
ValueCountFrequency (%)
0 62
0.2%
0.01 138
0.5%
0.02 88
0.3%
0.03 113
0.4%
0.04 86
0.3%

holiday_season
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:34.990088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length33
Median length33
Mean length2.5002142.5043
Min length22

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters250021475129
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowNoYes
2nd rowNoNo
3rd rowYesYes
4th rowYesNo
5th rowYesYes
ValueCountFrequency (%)
yes 500214
50.0%
no 499786
50.0%
ValueCountFrequency (%)
yes 15129
50.4%
no 14871
49.6%
2025-06-06T01:55:35.238265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15129
20.1%
e 15129
20.1%
s 15129
20.1%
N 14871
19.8%
o 14871
19.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75129
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15129
20.1%
e 15129
20.1%
s 15129
20.1%
N 14871
19.8%
o 14871
19.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75129
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15129
20.1%
e 15129
20.1%
s 15129
20.1%
N 14871
19.8%
o 14871
19.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75129
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15129
20.1%
e 15129
20.1%
s 15129
20.1%
N 14871
19.8%
o 14871
19.8%

season
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:35.449489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length66
Mean length5.5003225.501533333
Min length44

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters5500322165046
Distinct characters1414
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowSpringSummer
2nd rowSummerWinter
3rd rowWinterSpring
4th rowWinterSummer
5th rowSummerSpring
ValueCountFrequency (%)
winter 250307
25.0%
spring 250169
25.0%
fall 249839
25.0%
summer 249685
25.0%
ValueCountFrequency (%)
winter 7567
25.2%
summer 7535
25.1%
fall 7477
24.9%
spring 7421
24.7%
2025-06-06T01:55:35.780804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22523
13.6%
e 15102
9.2%
m 15070
9.1%
n 14988
9.1%
i 14988
9.1%
S 14956
9.1%
l 14954
9.1%
W 7567
 
4.6%
t 7567
 
4.6%
u 7535
 
4.6%
Other values (4) 29796
18.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 165046
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22523
13.6%
e 15102
9.2%
m 15070
9.1%
n 14988
9.1%
i 14988
9.1%
S 14956
9.1%
l 14954
9.1%
W 7567
 
4.6%
t 7567
 
4.6%
u 7535
 
4.6%
Other values (4) 29796
18.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 165046
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22523
13.6%
e 15102
9.2%
m 15070
9.1%
n 14988
9.1%
i 14988
9.1%
S 14956
9.1%
l 14954
9.1%
W 7567
 
4.6%
t 7567
 
4.6%
u 7535
 
4.6%
Other values (4) 29796
18.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 165046
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22523
13.6%
e 15102
9.2%
m 15070
9.1%
n 14988
9.1%
i 14988
9.1%
S 14956
9.1%
l 14954
9.1%
W 7567
 
4.6%
t 7567
 
4.6%
u 7535
 
4.6%
Other values (4) 29796
18.1%

weekend
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:35.958349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length33
Median length22
Mean length2.4993332.496766667
Min length22

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters249933374903
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowYesYes
2nd rowYesYes
3rd rowYesYes
4th rowNoYes
5th rowYesNo
ValueCountFrequency (%)
no 500667
50.1%
yes 499333
49.9%
ValueCountFrequency (%)
no 15097
50.3%
yes 14903
49.7%
2025-06-06T01:55:36.360098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
N 15097
20.2%
o 15097
20.2%
Y 14903
19.9%
e 14903
19.9%
s 14903
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 74903
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
N 15097
20.2%
o 15097
20.2%
Y 14903
19.9%
e 14903
19.9%
s 14903
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 74903
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
N 15097
20.2%
o 15097
20.2%
Y 14903
19.9%
e 14903
19.9%
s 14903
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 74903
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
N 15097
20.2%
o 15097
20.2%
Y 14903
19.9%
e 14903
19.9%
s 14903
19.9%

customer_support_calls
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct2020
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean9.4962699.477766667
 Full DatasetSimple Random Sample
Minimum00
Maximum1919
Zeros497551519
Zeros (%)5.0%5.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:36.528092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile10
Q144
median99
Q31414
95-th percentile1818
Maximum1919
Range1919
Interquartile range (IQR)1010

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation5.7612327915.755433072
Coefficient of variation (CV)0.6066838240.6072562529
Kurtosis-1.204539564-1.200263937
Mean9.4962699.477766667
Median Absolute Deviation (MAD)55
Skewness0.0015720255060.004708694951
Sum9496269284333
Variance33.1918032733.12500985
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:36.712815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3 50608
 
5.1%
8 50350
 
5.0%
4 50334
 
5.0%
12 50312
 
5.0%
2 50158
 
5.0%
11 50151
 
5.0%
16 50087
 
5.0%
13 50074
 
5.0%
9 50053
 
5.0%
7 50050
 
5.0%
Other values (10) 497823
49.8%
ValueCountFrequency (%)
7 1560
 
5.2%
17 1550
 
5.2%
3 1549
 
5.2%
12 1541
 
5.1%
10 1524
 
5.1%
9 1523
 
5.1%
0 1519
 
5.1%
13 1516
 
5.1%
6 1506
 
5.0%
16 1499
 
5.0%
Other values (10) 14713
49.0%
ValueCountFrequency (%)
0 49755
5.0%
1 49530
5.0%
2 50158
5.0%
3 50608
5.1%
4 50334
5.0%
ValueCountFrequency (%)
0 1519
5.1%
1 1474
4.9%
2 1484
4.9%
3 1549
5.2%
4 1487
5.0%
ValueCountFrequency (%)
0 1519
0.2%
1 1474
0.1%
2 1484
0.1%
3 1549
0.2%
4 1487
0.1%
ValueCountFrequency (%)
0 49755
165.9%
1 49530
165.1%
2 50158
167.2%
3 50608
168.7%
4 50334
167.8%

email_subscriptions
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:37.722968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length33
Median length22
Mean length2.4999382.4956
Min length22

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters249993874868
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowNoYes
2nd rowNoYes
3rd rowYesYes
4th rowNoYes
5th rowNoNo
ValueCountFrequency (%)
no 500062
50.0%
yes 499938
50.0%
ValueCountFrequency (%)
no 15132
50.4%
yes 14868
49.6%
2025-06-06T01:55:38.149181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
N 15132
20.2%
o 15132
20.2%
Y 14868
19.9%
e 14868
19.9%
s 14868
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 74868
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
N 15132
20.2%
o 15132
20.2%
Y 14868
19.9%
e 14868
19.9%
s 14868
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 74868
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
N 15132
20.2%
o 15132
20.2%
Y 14868
19.9%
e 14868
19.9%
s 14868
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 74868
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
N 15132
20.2%
o 15132
20.2%
Y 14868
19.9%
e 14868
19.9%
s 14868
19.9%

app_usage
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:38.438276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length44
Mean length4.3342994.3401
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters4334299130203
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowHighLow
2nd rowHighMedium
3rd rowLowMedium
4th rowLowLow
5th rowMediumLow
ValueCountFrequency (%)
medium 333822
33.4%
low 333345
33.3%
high 332833
33.3%
ValueCountFrequency (%)
medium 10086
33.6%
low 9969
33.2%
high 9945
33.1%
2025-06-06T01:55:38.953639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 20031
15.4%
M 10086
7.7%
e 10086
7.7%
d 10086
7.7%
u 10086
7.7%
m 10086
7.7%
L 9969
7.7%
o 9969
7.7%
w 9969
7.7%
H 9945
7.6%
Other values (2) 19890
15.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 130203
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 20031
15.4%
M 10086
7.7%
e 10086
7.7%
d 10086
7.7%
u 10086
7.7%
m 10086
7.7%
L 9969
7.7%
o 9969
7.7%
w 9969
7.7%
H 9945
7.6%
Other values (2) 19890
15.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 130203
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 20031
15.4%
M 10086
7.7%
e 10086
7.7%
d 10086
7.7%
u 10086
7.7%
m 10086
7.7%
L 9969
7.7%
o 9969
7.7%
w 9969
7.7%
H 9945
7.6%
Other values (2) 19890
15.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 130203
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 20031
15.4%
M 10086
7.7%
e 10086
7.7%
d 10086
7.7%
u 10086
7.7%
m 10086
7.7%
L 9969
7.7%
o 9969
7.7%
w 9969
7.7%
H 9945
7.6%
Other values (2) 19890
15.3%

website_visits
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.51295149.65466667
 Full DatasetSimple Random Sample
Minimum00
Maximum9999
Zeros10111284
Zeros (%)1.0%0.9%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:39.189813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile45
Q12524
median5050
Q37575
95-th percentile9595
Maximum9999
Range9999
Interquartile range (IQR)5051

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation28.8697769928.88947037
Coefficient of variation (CV)0.58307526440.5818077597
Kurtosis-1.199464505-1.200698234
Mean49.51295149.65466667
Median Absolute Deviation (MAD)2525
Skewness-0.0006306812576-0.005383316675
Sum495129511489640
Variance833.4640237834.6014983
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:39.444354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 10304
 
1.0%
95 10250
 
1.0%
50 10235
 
1.0%
62 10177
 
1.0%
45 10175
 
1.0%
13 10166
 
1.0%
38 10160
 
1.0%
84 10147
 
1.0%
98 10136
 
1.0%
93 10132
 
1.0%
Other values (90) 898118
89.8%
ValueCountFrequency (%)
43 334
 
1.1%
21 333
 
1.1%
84 332
 
1.1%
55 330
 
1.1%
13 329
 
1.1%
66 327
 
1.1%
50 327
 
1.1%
89 325
 
1.1%
22 324
 
1.1%
1 323
 
1.1%
Other values (90) 26716
89.1%
ValueCountFrequency (%)
0 10111
1.0%
1 9997
1.0%
2 9933
1.0%
3 10007
1.0%
4 9969
1.0%
ValueCountFrequency (%)
0 284
0.9%
1 323
1.1%
2 294
1.0%
3 309
1.0%
4 264
0.9%
ValueCountFrequency (%)
0 284
< 0.1%
1 323
< 0.1%
2 294
< 0.1%
3 309
< 0.1%
4 264
< 0.1%
ValueCountFrequency (%)
0 10111
33.7%
1 9997
33.3%
2 9933
33.1%
3 10007
33.4%
4 9969
33.2%

social_media_engagement
['Text', 'Text']

 Full DatasetSimple Random Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:39.673959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSimple Random Sample
Max length66
Median length44
Mean length4.3320574.341566667
Min length33

Characters and Unicode

 Full DatasetSimple Random Sample
Total characters4332057130247
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSimple Random Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSimple Random Sample
1st rowHighHigh
2nd rowMediumHigh
3rd rowMediumLow
4th rowLowLow
5th rowLowLow
ValueCountFrequency (%)
low 334073
33.4%
medium 333065
33.3%
high 332862
33.3%
ValueCountFrequency (%)
medium 10113
33.7%
low 9979
33.3%
high 9908
33.0%
2025-06-06T01:55:39.986611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20021
15.4%
M 10113
7.8%
e 10113
7.8%
d 10113
7.8%
u 10113
7.8%
m 10113
7.8%
L 9979
7.7%
o 9979
7.7%
w 9979
7.7%
H 9908
7.6%
Other values (2) 19816
15.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130247
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20021
15.4%
M 10113
7.8%
e 10113
7.8%
d 10113
7.8%
u 10113
7.8%
m 10113
7.8%
L 9979
7.7%
o 9979
7.7%
w 9979
7.7%
H 9908
7.6%
Other values (2) 19816
15.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130247
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20021
15.4%
M 10113
7.8%
e 10113
7.8%
d 10113
7.8%
u 10113
7.8%
m 10113
7.8%
L 9979
7.7%
o 9979
7.7%
w 9979
7.7%
H 9908
7.6%
Other values (2) 19816
15.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130247
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20021
15.4%
M 10113
7.8%
e 10113
7.8%
d 10113
7.8%
u 10113
7.8%
m 10113
7.8%
L 9979
7.7%
o 9979
7.7%
w 9979
7.7%
H 9908
7.6%
Other values (2) 19816
15.2%

days_since_last_purchase
Real number (ℝ)

 Full DatasetSimple Random Sample
Distinct365365
Distinct (%)< 0.1%1.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean182.027559181.8529
 Full DatasetSimple Random Sample
Minimum00
Maximum364364
Zeros276885
Zeros (%)0.3%0.3%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T01:55:40.165329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSimple Random Sample
Minimum00
5-th percentile1817
Q19190
median182182
Q3273273
95-th percentile346346
Maximum364364
Range364364
Interquartile range (IQR)182183

Descriptive statistics

 Full DatasetSimple Random Sample
Standard deviation105.3645979105.4297149
Coefficient of variation (CV)0.57883871230.579752728
Kurtosis-1.199912738-1.200899883
Mean182.027559181.8529
Median Absolute Deviation (MAD)9191
Skewness-0.0005543132091-0.001491041616
Sum1820275595455587
Variance11101.6984811115.42478
MonotonicityNot monotonicNot monotonic
2025-06-06T01:55:40.414859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 2916
 
0.3%
72 2890
 
0.3%
98 2888
 
0.3%
252 2869
 
0.3%
364 2867
 
0.3%
6 2862
 
0.3%
325 2857
 
0.3%
136 2843
 
0.3%
267 2833
 
0.3%
239 2832
 
0.3%
Other values (355) 971343
97.1%
ValueCountFrequency (%)
193 103
 
0.3%
57 103
 
0.3%
158 103
 
0.3%
21 102
 
0.3%
260 101
 
0.3%
118 101
 
0.3%
219 100
 
0.3%
208 100
 
0.3%
129 99
 
0.3%
6 98
 
0.3%
Other values (355) 28990
96.6%
ValueCountFrequency (%)
0 2768
0.3%
1 2752
0.3%
2 2701
0.3%
3 2709
0.3%
4 2786
0.3%
ValueCountFrequency (%)
0 85
0.3%
1 90
0.3%
2 80
0.3%
3 90
0.3%
4 84
0.3%
ValueCountFrequency (%)
0 85
< 0.1%
1 90
< 0.1%
2 80
< 0.1%
3 90
< 0.1%
4 84
< 0.1%
ValueCountFrequency (%)
0 2768
9.2%
1 2752
9.2%
2 2701
9.0%
3 2709
9.0%
4 2786
9.3%